CN114882986B

CN114882986B - Information distribution processing method and device and computer readable storage medium

Info

Publication number: CN114882986B
Application number: CN202210811912.1A
Authority: CN
Inventors: 杨翠; 刘万利; 谢静; 田言
Original assignee: West China Hospital of Sichuan University
Current assignee: West China Hospital of Sichuan University
Priority date: 2022-07-12
Filing date: 2022-07-12
Publication date: 2022-11-08
Anticipated expiration: 2042-07-12
Also published as: CN114882986A

Abstract

The embodiment of the invention discloses an information distribution processing method, an information distribution processing device and a computer readable storage medium; after acquiring a medical order information flow, transmission parameters of the medical order information flow and current processing information of a medical equipment group, the medical equipment group comprises at least two pieces of medical equipment and a processing queue corresponding to the medical equipment, then, generating state transition characteristics of the medical equipment group according to the transmission parameters and the processing parameters, calculating steady-state probability of the medical equipment group for processing the medical order information flow in a preset state based on the state transition characteristics, then, determining segmentation parameters of the medical order information flow according to the steady-state probability, segmenting the medical order information flow based on the segmentation parameters to obtain a target medical order information flow corresponding to the processing queue, and sending the target medical order information flow to the processing queue so that the medical equipment group processes the target medical order information flow; the scheme can greatly improve the efficiency of information distribution processing.

Description

Information distribution processing method and device and computer readable storage medium

Technical Field

The present invention relates to the field of communications technologies, and in particular, to an information distribution processing method and apparatus, and a computer-readable storage medium.

Background

In recent years, with the development of information in hospitals, more and more information flows are generated which need to be processed, for example, medical order information flows corresponding to the requirements of detection, operation, outpatient service and the like generated by registration or other reservation forms. The existing information distribution processing method is usually to distribute the information randomly or evenly to each processing queue for processing.

In the process of research and practice on the prior art, the inventor of the present invention finds that, in the existing information distribution processing method, due to different processing parameters of medical devices for different queues of medical order information, distribution to the medical devices randomly or averagely may cause unbalanced flow of medical order information processed by a medical device group, and thus, the efficiency of information processing may be greatly reduced.

Disclosure of Invention

The embodiment of the invention provides an information distribution processing method, an information distribution processing device and a computer readable storage medium, which can improve the information processing efficiency.

An information distribution processing method comprises the following steps:

acquiring a medical order information flow, transmission parameters of the medical order information flow and current processing information of a medical equipment group, wherein the medical equipment group comprises at least two pieces of medical equipment and a processing queue corresponding to the medical equipment, and the current processing information comprises processing parameters of the medical equipment for the medical order information in the processing queue;

generating state transition characteristics of the medical equipment group according to the transmission parameters and the processing parameters, wherein the state transition characteristics are used for indicating the medical equipment group to process state transition information of a medical order information flow;

based on the state transition characteristics, calculating a steady-state probability of the medical equipment group processing the medical order information flow in a preset state, wherein the steady-state probability is used for indicating the probability of the medical equipment group processing a preset amount of medical order information;

determining segmentation parameters of the medical order information flow according to the steady-state probability;

segmenting the medical order information flow based on the segmentation parameters to obtain a target medical order information flow corresponding to the processing queue;

and sending the target medical order information flow to the processing queue so that the medical equipment group can process the target medical order information flow.

Correspondingly, an embodiment of the present invention provides an information offloading processing apparatus, including:

the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a medical order information stream, transmission parameters of the medical order information stream and current processing information of a medical equipment group, the medical equipment group comprises at least two pieces of medical equipment and a processing queue corresponding to the medical equipment, and the current processing information comprises processing parameters of the medical equipment aiming at the medical order information in the processing queue;

the generating unit is used for generating state transition characteristics of the medical equipment group according to the transmission parameters and the processing parameters, and the state transition characteristics are used for indicating the medical equipment group to process state transition information of a medical order information flow;

the calculating unit is used for calculating the steady-state probability of the medical equipment group for processing the medical order information flow in a preset state based on the state transition characteristics, wherein the steady-state probability is used for indicating the probability of the medical equipment group for processing a preset amount of medical order information;

the determining unit is used for determining the segmentation parameters of the medical order information flow according to the steady-state probability;

the segmentation unit is used for segmenting the medical order information flow based on the segmentation parameters to obtain a target medical order information flow corresponding to the processing queue;

and the processing unit is used for sending the target medical order information flow to the processing queue so that the medical equipment group can process the target medical order information flow.

In addition, an embodiment of the present invention further provides a computer-readable storage medium, where multiple instructions are stored, and the instructions are suitable for being loaded by a processor to perform any step in any information distribution processing method provided in the embodiment of the present invention.

After a medical order information flow, transmission parameters of the medical order information flow and current processing information of a medical equipment group are obtained, the medical equipment group comprises at least two pieces of medical equipment and a processing queue corresponding to the medical equipment, the current processing information comprises processing parameters of the medical equipment aiming at the medical order information in the processing queue, then, according to the transmission parameters and the processing parameters, a state transition characteristic of the medical equipment group is generated and used for indicating the medical equipment group to process the state transition information of the medical order information flow, then, based on the state transition characteristic, a steady state probability of the medical equipment group in a preset state for processing the medical order information flow is calculated and used for indicating the probability of the medical equipment group processing the preset number of medical order information, then, according to the steady state probability, segmentation parameters of the medical order information flow are determined, the medical order information flow is segmented based on the segmentation parameters, a target medical order information flow corresponding to the processing queue is obtained, and the target medical order information flow is sent to the processing queue, so that the target medical equipment group processes the target medical order information flow; according to the scheme, the state transition characteristics of the medical equipment group are generated according to the transmission parameters and the processing parameters, the steady-state probability of processing the medical order information is calculated, then the medical order information flow is segmented according to the steady-state probability, the internal state of the medical equipment group is fully considered, the medical order information distribution is more balanced, and therefore the efficiency of information distribution processing can be greatly improved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.

Fig. 1 is a scene schematic diagram of an information distribution processing method according to an embodiment of the present invention;

fig. 2 is a schematic flow chart of an information distribution processing method according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of a state transition diagram provided by an embodiment of the present invention;

fig. 4 is another schematic flow chart of information distribution processing provided by the embodiment of the present invention;

FIG. 5 is a flowchart illustrating information distribution processing performed during a preoperative examination scenario according to an embodiment of the present invention;

fig. 6 is a schematic structural diagram of an information distribution processing apparatus according to an embodiment of the present invention;

fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.

The embodiment of the invention provides an information distribution processing method and device and a computer readable storage medium. The information distribution processing device may be integrated in an electronic device, and the electronic device may be a server or a terminal.

The server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as cloud service, a cloud database, cloud computing, a cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, network acceleration service (CDN), big data, an artificial intelligence platform, and the like. The terminal may be, but is not limited to, a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and the like. The terminal and the server may be directly or indirectly connected through wired or wireless communication, and the application is not limited herein.

For example, referring to fig. 1, taking an example that the information offloading processing apparatus is integrated in an electronic device, after the electronic device obtains a medical order information stream, a transmission parameter of the medical order information stream, and current processing information of a medical device group, the medical device group includes at least two medical devices and a processing queue corresponding to the medical devices, the processing information includes a processing parameter of the medical device for the medical order information in the processing queue, then, according to the transmission parameter and the processing parameter, a state transition characteristic of the medical device group is generated, the state transition characteristic is used for indicating the medical device group to process state transition information of the medical order information stream, then, based on the state transition characteristic, a steady state probability of the medical device group processing the medical order information stream in a preset state is calculated, the steady state probability is used for indicating a probability of the medical device group processing a preset number of medical order information, then, according to the steady state probability, a segmentation parameter of the medical order information stream is determined, the medical order information stream is segmented based on the segmentation parameter, a target medical order information stream corresponding to the processing queue is obtained, and the target medical device group processes the target medical order information stream.

The following are detailed descriptions. It should be noted that the following description of the embodiments is not intended to limit the preferred order of the embodiments.

The embodiment will be described from the perspective of an information distribution processing apparatus, which may be specifically integrated in an electronic device, where the electronic device may be a server or a terminal; the terminal may include a tablet Computer, a notebook Computer, a Personal Computer (PC), a wearable device, a virtual reality device, or other devices capable of performing information distribution processing.

An information distribution processing method comprises the following steps:

the method comprises the steps of obtaining a medical order information flow, transmission parameters of the medical order information flow and current processing information of a medical equipment group, wherein the medical equipment group comprises at least two medical equipment and a processing queue corresponding to the medical equipment, the processing information comprises processing parameters of the medical equipment aiming at the medical order information in the processing queue, state transition characteristics of the medical equipment group are generated according to the transmission parameters and the processing parameters, the state transition characteristics are used for indicating the state transition information of the medical equipment group for processing the medical order information flow, the steady state probability of the medical equipment group for processing the medical order information flow in a preset state is calculated based on the state transition characteristics, the steady state probability is used for indicating the probability of the medical equipment group for processing the preset number of medical order information, the segmentation parameters of the medical order information flow are determined according to the steady state probability, the medical order information flow is segmented based on the segmentation parameters, the target medical order information flow corresponding to the processing queue is obtained, and the target medical order information flow is sent to the processing queue, so that the medical equipment group processes the target medical order information flow.

As shown in fig. 2, the specific flow of the information distribution processing method is as follows:

101. acquiring a medical order information flow, transmission parameters of the medical order information flow and current processing information of a medical equipment group.

The medical order information flow may be a poisson flow generated by appointment events such as registration in a hospital, the poisson flow may be an event flow with stationarity, universality and non-aftereffect, for example, an examination requirement event flow formed by preoperative examination of a registration of a patient in the hospital may be formed, and the examination requirement event flow may be composed of examination requirement information meeting distribution of the poisson flow one by one. The transmission parameter of the medical order information stream may be understood as the arrival rate of the information to be processed in the information stream to be processed.

The medical device group includes at least two medical devices and processing queues corresponding to the medical devices, the medical devices may be software or hardware devices for processing medical order information, and the medical devices may process 1 piece of information of a medical order at a time, for example, taking the medical order information as medical detection request information, the medical devices may be various types of examination devices for examining a patient, and the like. The current processing information includes processing parameters of the medical devices for the medical order information in the processing queue, where the processing parameters may be a processing rate of each medical device in the medical device group for processing the medical order information, and may further include a capacity allocation ratio of each medical device for different processing queues.

For example, the medical order information flow and the transmission parameters of the medical order information flow may be directly obtained, for example, different users trigger medical order information processing requests on the terminal at different times, the medical order information requests may be processing information meeting target medical requirements, when there are medical order information processing requests triggered by multiple users at different times, the medical order information flow may be generated, the information distribution processing device receives each piece of medical order information in the medical order information flow, and according to the arrival time of each piece of medical order information, the transmission parameters of the medical order information flow may be determined, and the transmission parameters may be a fixed value. For the current processing information of the medical device group, the attribute information of the medical device group may be directly obtained, and the current processing information when the medical device processes the medical order information stream is extracted from the attribute information, where the current processing information may be real-time information or pre-configured configuration information. When the memory of the medical order information in the medical order information stream is large or the quantity of the medical order information is large, the medical order information stream can be indirectly acquired, for example, the medical order information stream is used for triggering an information processing request on a terminal, medical order information is generated according to the information processing request, the medical order information stream can be composed of a plurality of pieces of medical order information, the medical order information is stored, then the storage address of each piece of medical order information in the medical order information stream is sent to an information distribution processing device, the medical order information can be acquired in the terminal according to the storage address by the information distribution processing device, a user can further store the medical order information to a cloud service platform or a block chain through the terminal, then the storage address is sent to the information distribution processing device, and the information distribution processing device acquires the medical order information according to the storage address, so that the medical order information stream is acquired.

102. And generating the state transition characteristics of the to-be-treated medical equipment group according to the transmission parameters and the processing parameters.

The state transition characteristic may be a state transition diagram of the medical device group when processing each piece of medical order information in the medical order information flow.

For example, the target quantity of the medical order information in the medical order information flow within the preset time may be determined according to the transmission parameters, for example, the quantity of the medical order information arriving within a preset time is determined according to the transmission parameters in the medical order information flow, for example, the preset time may be one day, the quantity of the medical order information arriving within one day may be calculated according to the arrival rate λ of the medical order information flow, and the quantity is used as the target quantity of the maximum medical order information that needs to be processed by the medical device group within one day. Based on the processing parameters, simulating the medical order information of the target quantity processed by the medical equipment group to obtain the state transition information of the medical order information processed by the medical equipment to be processed, for example, according to the medical order informationAnd the target quantity of information, determining at least one processing path for processing the medical order information by the medical equipment group to obtain a processing path set, and simulating the medical equipment group to process the medical order information flow by adopting each processing path in the processing path set based on the processing parameters to obtain the state transition information of each medical equipment in the medical equipment group. Performing feature extraction on the state transition information to obtain state transition features of the medical equipment group, for example, a state transition diagram of medical order information of a processing target quantity of each processing path adopted by the medical equipment group may be constructed based on the state transition information, the medical order information requirement is used as preoperative examination request information of a patient, the number of processing queues 2 and a splitting coefficient α to be calculated are taken as an example, the state transition diagram may be as shown in fig. 3, and λ is an arrival rate of the medical order information, so that the arrival rate of the processing queue 1 is λ ₁ = α λ, arrival rate of processing queue 2 is λ ₂ = 1- α λ, β is the allocation ratio of the medical device a to the two processing queues, γ is the allocation ratio of the medical device B to the two processing queues, μ _A The processing rate for processing medical order information for medical device a, therefore, the processing rate of processing queue 1 may be μ _ A1= β μ _A The arrival rate of the processing queue 2 may be μ _A2 =(1-β) μ _A ，μ _B The processing rate for processing medical order information for medical device B, and thus, the processing rate for processing queue 1 may be μ _B1 =γμ _B The arrival rate of processing queue 2 may be μ _B2 =(1-γ) μ _B 。

Optionally, the status information of the flow of the medical order information processed by each medical device in the medical device group may be determined according to the transmission parameter and the processing parameter, for example, it may be determined that a processing event exists in the medical device group and the processing queue according to the transmission parameter, for example, the processing event may include 1 arrival of the medical order information in the

processing queue

1, 1 arrival of the medical order information in the processing queue 2, 1 arrival of the medical order information in the processing queue 1 processed by the medical device a, 1 arrival of the medical order information in the processing queue 2 processed by the medical device a, and 1 arrival of the medical order information in the processing queue 1 processed by the medical device B, and no arrival and processing of the medical order information. And simulating the medical equipment to process the processing event based on the processing parameters to obtain the state information of each medical equipment in the medical equipment group for processing the medical order information flow. And fusing the state information to obtain state transition information of the medical order information flow processed by the medical equipment, for example, determining a processing path of the medical equipment group for the medical order information flow based on the transmission parameter and the processing parameter, and fusing the state information of the medical equipment according to the processing path to obtain the state transition information of the medical order information flow processed by the medical order information. The state transition information is subjected to feature extraction to obtain state transition features of the medical device group, for example, a state transition diagram of the medical device group for processing the medical order information of the target quantity by using each processing path may be constructed based on the state transition information, and the state transition diagram may be as shown in fig. 3.

103. And according to the state transition characteristics, calculating the steady-state probability of the medical equipment group for processing the medical order information flow in the preset state.

Wherein the steady-state probability is used to indicate a probability that the medical device group processes a preset amount of medical order information.

For example, according to the state transition characteristics, processing balance information of the medical order information stream processed by the medical device group is determined, and the processing balance information indicates a processing balance relationship of each medical order information in the medical order information stream processed by the medical device group, for example, a balance equation between the arrival and the end of processing of each medical order information may be constructed according to the state transition diagram of the medical device group, and taking the case that the medical device group includes two serial medical devices, the balance equation may be as follows:

wherein λ is the arrival rate of the medical order information, λ ₁ To handle the arrival rate of queue 1, λ ₂ Beta is the allocation ratio of the medical equipment A to the two processing queues, and gamma is the allocation ratio of the medical equipment B to the two processing queues, mu, for the arrival rate of the processing queue 2 _A The processing rate for processing medical order information for medical device A may be μ _A1 =βμ _A The arrival rate of processing queue 2 may be μ _A2 =(1-β) μ _A ，μ _B For the processing rate at which medical device B processes medical order information, the processing rate of processing queue 1 may be μ _B1 =γμ _B The arrival rate of the processing queue 2 is μ _B2 =(1-γ) μ _B ，π _ij Is the steady state probability that the number of medical order information in the system of processing queue 1 is i, and the number of medical order information in the system of processing queue 2 is j in the current system.

The processing balance information is analyzed to obtain the initial steady-state probability of the medical order information flow processed by the medical equipment group in the preset state, wherein the preset state can be a stable state, and the conditions of the existence of the stable state can be lambda \8260, mu <1 and alpha lambda \8260, beta mu <1 and ((1-alpha) lambda \8260; (1-beta) mu) <1. For example, the initial steady-state probabilities in the equilibrium equations can be solved using a "Matrix-geometry" Method (neutrs' Matrix-Geometric Method). The initial steady-state probabilities are fused to obtain the steady-state probabilities of the medical equipment group for processing the medical order information streams in the preset state, for example, an initial steady-state probability set of each medical order information stream processed by the medical equipment group can be obtained by combining each initial steady-state probability, the initial steady-state probability set is used as the steady-state probability of the medical equipment group for processing the medical order information streams in the preset state, the initial steady-state probabilities can be classified, probability weights of each type can be obtained, the initial steady-state probabilities are weighted based on the probability weights, the weighted initial steady-state probabilities are fused, and the steady-state probabilities of the medical equipment group for processing the medical order information streams in the preset state can be obtained.

104. And determining the segmentation parameters of the medical order information flow according to the steady-state probability.

The dividing parameter may be parameter information such as a dividing ratio for dividing the medical order information stream into each processing queue.

For example, the steady-state probabilities may be classified according to the types of the processing queues to obtain target steady-state probabilities corresponding to the medical order information quantities in the processing queues, the target processing quantities of each processing queue within a preset time are calculated based on the target steady-state probabilities, and the segmentation parameters of the medical order information streams are determined according to the target processing quantities.

S1, classifying the steady-state probabilities according to the types of the processing queues to obtain target steady-state probabilities corresponding to the quantity of the medical order information in the processing queues.

For example, the steady-state probabilities are classified according to the type of the processing queue to obtain the target steady-state probabilities corresponding to the number of medical order information in the processing queue, for example, taking the processing queue including the processing queue 1 and the processing queue 2 as an example, the steady-state probabilities are divided into any number of medical order information in the processing queue 1 and any number of medical order information in the processing queue 2, for example, taking the medical order information in the processing queue 1 as an example, when 1 piece of medical order information exists in the processing queue 1, the target steady-state probability corresponding to the classification is pi ₁₀ 、π ₁₁ And pi ₁₂ When 1 piece of medical order information exists in the processing queue 2, the target steady-state probability of the corresponding classification can be pi ₀₁ 、π ₁₁ And pi ₂₁ And the like.

And S2, calculating the target processing quantity of each processing queue in preset time based on the target steady-state probability.

For example, based on the target steady-state probability, the target processing amount of each processing queue in the preset time is calculated, for example, for the processing queue 1, the target processing amount in the preset time may be calculated as the following formula:

wherein n is ₁ The number of containable medical device groups to be accessed from queue 1, n ₂ The number of containable items to be entered into the medical equipment group from queue 2, i the number of medical order information to be processed in queue 1, pi _ij Is the steady state probability that the number of medical order information in the system of processing queue 1 is i, and the number of medical order information in the system of processing queue 2 is j in the current system.

For the processing queue 2, the target processing amount in the preset time can be calculated by the following formula:

wherein n is ₁ The number of containers, n, for accessing the group of medical devices from queue 1 ₂ The number of containable medical equipment groups to be entered from queue 2, j is the number of medical order information to be processed in queue 2, pi _ij Is the steady state probability that the number of medical order information in the system of processing queue 1 is i, and the number of medical order information in the system of processing queue 2 is j in the current system.

And S3, determining the segmentation parameters of the medical order information flow according to the target processing quantity.

For example, the segmentation information of the medical order information stream may be determined according to the target processing quantity, for example, by taking a medical device group including 2 serial medical devices, each medical device corresponding to a processing queue as an example, the segmentation coefficient of the medical order information stream may be determined according to the ratio between the target quantities of the processing queue 1 and the processing queue 2, and may be calculated according to the following formula:

α=E(L ₁ )⁄E(L ₂ )

wherein α is a segmentation coefficient of the medical order information stream. When the number of the processing queues exceeds 2, the target processing numbers of each processing queue can be compared, so that a plurality of segmentation coefficients for segmenting the medical order information can be obtained, and the segmentation coefficients are used as segmentation information. The segmentation information may be parameter information for segmenting the medical order information into a plurality of sub-information streams, and may be information such as a segmentation ratio, a segmentation time, and a segmentation type.

Extracting an initial splitting ratio between the target processing quantities of each processing queue from the splitting information, and determining the splitting parameters corresponding to the processing queues according to the initial splitting ratio, for example, when the number of the processing queues is two, the splitting parameters corresponding to the processing queues can be directly determined according to the initial splitting ratio, for example, when the initial splitting ratio is 1. When the processing queues have more than two, the initial splitting is fused, and the splitting parameter corresponding to each processing queue can be obtained, for example, there are three processing queues, processing queue a, processing queue B, and processing queue C, and the initial splitting ratio between processing queue a and processing queue B is 1: 4, the split ratios can be fused, and the split parameters corresponding to the processing queue a, the processing queue B and the processing queue C can be determined to be 0.3, 0.3 and 0.4 respectively.

Optionally, after the segmentation information of the medical order information stream is determined, the segmentation information may be checked, so the information offloading processing method may further include:

according to the segmentation information, first processing time of the medical equipment group for processing the medical order information flow is calculated, target waiting time of the medical order information in the medical equipment group is extracted from the first processing time, and when the target waiting time does not exceed a preset waiting time threshold value, a segmentation coefficient corresponding to a processing queue is identified in the segmentation information.

For example, a first processing time for processing the medical order information by the medical device group may be calculated according to the segmentation information, for example, the processing quantity information of the medical device group to the segmented medical order information flow is determined according to the segmentation information, the processing quantity information may include an average processing quantity of the medical order information in the medical device, and the first processing time for each medical order information of the segmented medical order information flow by the medical device group is calculated based on the processing parameters, for example, the processing time may be calculated by a target processing quantity of the processing queue based on the following formula:

wherein W is the first processing time, lambda is the arrival rate of the medical order information, n is the quantity of the medical order information in the medical equipment, and pi _ij Is the steady state probability that the number of medical order information in the system of processing queue 1 is i, and the number of medical order information in the system of processing queue 2 is j in the current system.

Extracting a target waiting time of the medical order information in the medical equipment group from the first processing time, for example, calculating a basic processing time of the medical equipment group for processing a medical order information stream according to the processing parameter, and extracting a target waiting time of the medical order information in the medical equipment from the first processing time based on the basic processing time, for example, subtracting the basic processing time from the first processing time to obtain the target waiting time, which may specifically adopt the following formula:

wherein,

for the base processing time, T is the target latency.

When the target waiting time does not exceed the preset waiting time threshold, the segmentation information is determined to have no problem, and therefore the segmentation parameters corresponding to the processing queue are identified in the segmentation information.

Optionally, the split information may be checked according to a processing level of the medical order information stream, and therefore the information splitting processing method may further include:

acquiring attribute information of the medical order information flow, determining the processing grade of the medical order information flow according to the attribute information, calculating second processing time for processing the medical order information flow by the medical equipment group based on the segmentation information, determining target processing time of the medical order information flow according to the processing grade, and identifying segmentation parameters corresponding to the processing queue in the segmentation information when the second processing time does not exceed the target processing time.

For example, attribute information such as a required type, a required quantity, and a required object of the medical order information flow may be acquired, and for example, by taking the medical order information flow as a patient preoperative examination request information flow, a disease type, an operation appointment time, an examination item type, and information of the patient himself/herself of the patient may be acquired as the attribute information. Determining a processing level of the medical order information stream according to the attribute information, for example, classifying the attribute information, weighting the classified attribute information to obtain a weighted value of the attribute information, determining a processing level of the medical order information stream according to the weighted value of the attribute information, for example, matching the weighted value with a numerical value interval corresponding to each processing level, and taking the processing level corresponding to the numerical value interval successfully matched as the processing level of the medical order information stream, wherein the processing level may include a plurality of processing levels, for example, the processing levels may include a first processing level, a second processing level, a third processing level, and the like, and the processing priority of the medical order information stream corresponding to each processing level is different. And determining the target processing time of the medical order information stream according to the processing grade, for example, screening the processing time corresponding to the processing grade from a preset processing time set to be used as the target processing time of the medical order information. Based on the segmentation information, the second processing time for the medical device group to process the medical order information stream is calculated in the same manner as described above, and is not described herein again. When the second processing time does not exceed the target processing time, it can be determined that there is no problem with the segmentation information, and thus the segmentation parameters corresponding to the processing are identified in the segmentation information.

105. And segmenting the medical order information flow based on the segmentation parameters to obtain a target medical order information flow corresponding to the processing queue.

For example, according to the segmentation parameters and the arrival times of the medical order information, the medical order information streams are marked, corresponding processing queues are respectively marked, and the marked medical order information streams are segmented, so that target medical order information streams corresponding to the processing queues can be obtained, for example, taking the segmentation parameter as 1.

106. And sending the target medical order information flow to a processing queue so that the medical equipment group can process the target medical order information flow.

For example, the segmented target medical order information flow is sent to a corresponding processing queue, so that the medical device corresponding to the processing queue processes the target medical order information flow, for example, the medical device processes the medical order information in the processing queue corresponding to the medical device according to a preset processing path, sends the medical order information in the processed target medical order information flow to the next medical device according to the preset processing path, and after receiving the medical order information, the next medical device processes the medical order information according to the processing parameters corresponding to the processing queue in which the medical order information is located, and after completing the processing, continues to send the processed medical order information flow to the next medical device until each medical device in the medical device group completes the processing of the medical order information.

As can be seen from the above, after acquiring a medical order information stream, transmission parameters of the medical order information stream, and current processing information of a medical device group, the medical device group includes at least two medical devices and a processing queue corresponding to the medical devices, the current processing information includes processing parameters of the medical devices for the medical order information in the processing queue, then, according to the transmission parameters and the processing parameters, a state transition characteristic of the medical device group is generated, the state transition characteristic is used to indicate the medical device group to process state transition information of the medical order information stream, then, based on the state transition characteristic, a steady state probability of the medical device group processing the medical order information stream in a preset state is calculated, the steady state probability is used to indicate a probability of the medical device group processing a preset number of pieces of medical order information, then, according to the steady state probability, a segmentation parameter of the medical order information stream is determined, the medical order information stream is segmented based on the segmentation parameter, a target medical order information stream corresponding to the processing queue is obtained, and the target medical order information stream is sent to the processing queue, so that the medical device group processes the target order information stream; according to the scheme, the state transition characteristics of the medical equipment group are generated according to the transmission parameters and the processing parameters, the steady-state probability of processing the medical order information is calculated, then the medical order information flow is segmented according to the steady-state probability, the internal state of the medical equipment group is fully considered, and the medical order information distribution is more balanced, so that the efficiency of information distribution processing can be greatly improved.

The method described in the above examples is further illustrated in detail below by way of example.

In this embodiment, the information distribution processing apparatus is specifically integrated in an electronic device, the electronic device is a server, and the medical device group includes two serial medical devices and a processing queue corresponding to the medical devices.

As shown in fig. 4, an information distribution processing method specifically includes the following steps:

201. the server obtains a medical order information flow, transmission parameters of the medical order information flow and current processing information of the medical equipment group.

For example, different users trigger medical order information processing requests on the terminal at different times, the medical order information processing requests can be processing information meeting target medical requirements, when the medical order information processing requests triggered by the users at different times exist, a medical order information stream can be generated, the server receives each piece of medical order information in the medical order information stream, and transmission parameters of the medical order information stream can be determined according to the arrival time of each piece of medical order information. For the current processing information of the medical device group, the attribute information of the medical device group may be directly obtained, and the current processing information when the medical device processes the medical order information stream is extracted from the attribute information, where the current processing information may be real-time information or pre-configured configuration information. When the memory of the medical order information in the medical order information flow is large or the quantity of the medical order information is large, the medical order information is stored, then the storage address of each piece of medical order information in the medical order information flow is sent to the server, and the server can obtain the medical order information in the terminal according to the storage address, so that the medical order information flow is obtained.

202. And the server generates the state transition characteristics of the to-be-treated medical equipment group according to the transmission parameters and the processing parameters.

For example, the server determines the quantity of the medical order information arriving within a preset time according to the transmission parameters of the medical order information stream, for example, the preset time may be one day, and the quantity of the medical order information arriving within one day may be calculated according to the arrival rate λ of the medical order information stream, and the quantity is used as the target quantity of the maximum medical order information that needs to be processed by the medical device group within one day. Determining at least one processing path of the medical order information processed by the medical equipment group according to the target quantity of the medical order information to obtain a processing path set, and simulating the medical equipment group to process the medical order information flow by adopting each processing path in the processing path set based on the processing parameters to obtain the state transition information of each medical equipment in the medical equipment group. And constructing a state transition diagram of the medical order information of the medical equipment group processing target quantity by adopting each processing path based on the state transition information.

Optionally, the server may further determine, according to the transmission parameter, that a processing event exists in the medical device group and the processing queue, where the processing event may include that 1 piece of medical order information arrives in the

processing queue

1, 1 piece of medical order information arrives in the processing queue 2, the medical device a processes 1 piece of medical order information arrived from the processing queue 1, the medical device a processes 1 piece of medical order information arrived from the processing queue 2, and the medical device B processes 1 piece of medical order information arrived from the processing queue 1, and no medical order information arrives and is processed. And determining a processing path of the medical equipment group for the medical order information flow based on the transmission parameters and the processing parameters, and fusing the state information of the medical equipment according to the processing path to obtain the state transition information of the medical order information processing medical order information flow. Constructing a state transition diagram of the medical order information of the medical equipment group adopting each processing path to process the target quantity based on the state transition information,

203. and the server calculates the steady-state probability of the medical equipment group for processing the medical order information flow in the preset state according to the state transition characteristics.

For example, the server constructs a balance equation between the arrival and the end of processing for each piece of medical order information from the state transition diagram for the medical device group, which may be as follows:

wherein, lambda is the arrival rate of the medical order information, lambda ₁ To handle the arrival rate of queue 1, λ ₂ Beta is the allocation ratio of the medical equipment A to the two processing queues, and gamma is the allocation ratio of the medical equipment B to the two processing queues, mu, for the arrival rate of the processing queue 2 _A Is medical equipment AThe processing rate of the medical order information, the processing rate of the processing queue 1, may be μ _A1 =βμ _A The arrival rate of processing queue 2 may be μ _A2 =(1-β) μ _A ，μ _B For the processing rate of medical device B processing medical order information, the processing rate of processing queue 1 may be μ _ B1= γ μ _ B, and the arrival rate of processing queue 2 is μ _B2 =(1-γ) μ _B ，π _ij Is the steady state probability that the number of medical order information in the system of processing queue 1 is i, and the number of medical order information in the system of processing queue 2 is j in the current system.

The server analyzes the processing balance information to obtain an initial steady-state probability of the medical equipment group for processing the medical order information flow in a preset state, for example, the initial steady-state probability in the balance equation can be solved by adopting a matrix geometry method. Combining the initial steady-state probabilities to obtain an initial steady-state probability set of each medical order information in the medical order information flow processed by the medical equipment group, taking the initial steady-state probability set as the steady-state probability of the medical order information flow processed by the medical equipment group in a preset state, classifying the initial steady-state probabilities, obtaining probability weights of each type, weighting the initial steady-state probabilities based on the probability weights, fusing the weighted initial steady-state probabilities, and obtaining the steady-state probability of the medical order information flow processed by the medical equipment group in the preset state.

204. And the server classifies the steady-state probability according to the type of the processing queue to obtain the target steady-state probability corresponding to the quantity of the medical order information in the processing queue.

For example, the server divides the steady-state probability into any number of pieces of medical order information in the processing queue 1 and any number of pieces of medical order information in the processing queue 2, for example, taking the medical order information in the processing queue 1 as an example, when 1 piece of medical order information exists in the processing queue 1, the target steady-state probability of the corresponding classification is pi ₁₀ 、π ₁₁ And pi ₁₂ When 1 piece of medical order information exists in the processing queue 2, the corresponding classified object steady-state summary is obtainedThe ratio may be pi ₀₁ 、π ₁₁ And pi ₂₁ And so on.

205. And the server calculates the target processing quantity of each processing queue in preset time based on the target steady-state probability.

For example, the server calculates the target processing amount of each processing queue in the preset time based on the target steady-state probability, for example, for processing queue 1, the target processing amount in the preset time may be calculated as the following formula:

wherein n is ₁ The number of containable medical device groups to be accessed from queue 1, n ₂ The number of containable items to be entered into the group of medical devices from queue 2, i the number of medical order information to be processed in queue 1, π _ij Is the steady state probability that the number of medical order information in the system of processing queue 1 is i, and the number of medical order information in the system of processing queue 2 is j in the current system.

wherein n is ₁ The number of containable medical device groups to be accessed from queue 1, n ₂ The number of containable medical equipment groups to be entered from queue 2, j is the number of medical order information to be processed in queue 2, pi _ij Is the steady state probability that the number of medical order information in the system of processing queue 1 is i, and the number of medical order information in the system of processing queue 2 is j in the current system.

206. And the server determines the segmentation parameters of the medical order information flow according to the target processing quantity.

For example, a segmentation factor for the medical order information stream is determined based on the ratio between the target quantities of the process queue 1 and the process queue 2, and may be calculated, for example, by the following formula:

α=E(L ₁ )⁄E(L ₂ )

wherein α is a segmentation coefficient of the medical order information stream. When the number of the processing queues exceeds 2, the target processing numbers of each processing queue can be compared, so that a plurality of segmentation coefficients for segmenting the medical order information can be obtained, and the segmentation coefficients are used as segmentation information. The segmentation information may be parameter information for segmenting the medical order information into a plurality of sub-information streams, and may be, for example, information such as a segmentation ratio, a segmentation time, and a segmentation type.

And the server extracts an initial splitting ratio between the target processing quantities of each processing queue from the splitting information, and determines the splitting parameters corresponding to the processing queues according to the initial splitting ratio.

Optionally, after determining the segmentation information of the medical order information stream, the segmentation information may be further checked, for example, according to the segmentation information, processing quantity information of the medical device group on the segmented medical order information stream is determined, where the processing quantity information may include an average processing quantity of the medical order information in the medical device, and based on the processing parameters, a first processing time of the medical device group for each piece of medical order information of the segmented medical order information stream is respectively calculated, for example, the processing time may be calculated by a target processing quantity of a processing queue based on the following formula:

Extracting a target waiting time of the medical order information in the medical device group from the first processing time, for example, calculating a basic processing time for processing a medical order information stream by the medical device group according to the processing parameter, and extracting a target waiting time of the medical order information in the medical device group from the first processing time based on the basic processing time, for example, subtracting the basic processing time from the first processing time to obtain the target waiting time, which may specifically adopt the following formula:

wherein,

for the base processing time, T is the target latency.

Optionally, the segmentation information may be verified according to a processing level of the medical order information stream, for example, by taking the medical order information stream as a preoperative examination request information stream of the patient, a disease type, an operation appointment time, an examination item type of the patient, information of the patient himself/herself, and the like may be acquired as the attribute information. Classifying the attribute information, weighting the classified attribute information to obtain a weighted value of the attribute information, matching the weighted value with a numerical value interval corresponding to each processing grade, and taking a processing grade corresponding to a numerical value interval successfully matched as a processing grade of the medical order information stream, wherein the processing grade can comprise a plurality of processing grades, and screening out processing time corresponding to the processing grade from a preset processing time set to be used as target processing time of the medical order information. Based on the segmentation information, the second processing time for the medical device group to process the medical order information stream is calculated in the same manner as described above, and is not described herein again. When the second processing time does not exceed the target processing time, it is determined that there is no problem with the segmentation information, and thus the segmentation parameters corresponding to the processing are identified in the segmentation information.

207. The server segments the medical order information flow based on the segmentation parameters to obtain a target medical order information flow corresponding to the processing queue.

For example, according to the segmentation parameters and the arrival time of the medical order information, the medical order information streams are marked, corresponding processing queues are respectively marked, and the marked medical order information streams are segmented, so that target medical order information streams corresponding to the processing queues can be obtained.

208. The server sends the target medical order information stream to a processing queue so that the medical equipment group processes the target medical order information stream.

For example, the segmented target medical order information flow is sent to a corresponding processing queue, the medical device processes the medical order information in the processing queue corresponding to the medical device according to a preset processing path, the medical order information in the processed target medical order information flow is sent to the next medical device according to the preset processing path, the next medical device processes the medical order information according to the processing parameters corresponding to the processing queue where the medical order information is located after receiving the medical order information, and after the processing is completed, the medical order information is continuously sent to the next medical device until each medical device in the medical device group completes the processing of the medical order information.

As can be seen from the above, after the server in this embodiment acquires the medical order information stream, the transmission parameters of the medical order information stream, and the current processing information of the medical equipment group, where the medical equipment group includes at least two medical equipments and a processing queue corresponding to the medical equipments, and the current processing information includes processing parameters of the medical equipment for the medical order information in the processing queue, then, according to the transmission parameters and the processing parameters, a state transition characteristic of the medical equipment group is generated, where the state transition characteristic is used to indicate state transition information of the medical equipment group for processing the medical order information stream, then, based on the state transition characteristic, a steady state probability of the medical equipment group for processing the medical order information stream in a preset state is calculated, where the steady state probability is used to indicate a probability of the medical equipment group for processing a preset number of pieces of medical order information, then, according to the steady state probability, a segmentation parameter of the medical order information stream is determined, the medical order information stream is segmented based on the segmentation parameter, a target medical order information stream corresponding to the processing queue is obtained, and the target medical order information stream is sent to the processing queue, so that the target medical equipment group processes the target medical order information stream; according to the scheme, the state transition characteristics of the medical equipment group are generated according to the transmission parameters and the processing parameters, the steady-state probability of processing the medical order information is calculated, then the medical order information flow is segmented according to the steady-state probability, the internal state of the medical equipment group is fully considered, the medical order information distribution is more balanced, and therefore the efficiency of information distribution processing can be greatly improved.

In the embodiment, the information distribution processing device is integrated in an electronic device, the electronic device is a server, the medical order information flow is an examination request information flow reserved by a patient before an operation, the medical order information is an examination request information, the medical device group is two serial examination service desks, each examination service desk comprises a processing queue, and information processing is exemplified by distributing the examination request information flow for the examination before the operation of the patient to different processing queues.

The method comprises the steps that each patient or an accompanying person of the patient inputs personal information, examination item information and the like of the patient at a terminal to carry out preoperative examination reservation, different time periods are reserved respectively to carry out preoperative examination, so that an examination request is triggered, the terminal generates examination request information according to the examination request and sends the examination request information to a server, an examination request information stream can be formed due to the fact that a plurality of examination request information of different time periods exist, the server can receive the examination request information stream sent by the terminal, and the arrival rate of the examination request information stream is obtained to serve as a transmission parameter. The server may further obtain real-time service information or preset service configuration information of the inspection service desk group as the inspection information, and the inspection information may further include processing parameters such as a capacity allocation ratio and a processing rate of the inspection service desk for each processing queue.

The server determines the target number of the examination request information needing to be processed in an examination time period according to the arrival rate of the examination request information flow, simulates the patients corresponding to the examination request information of the examination service desk for examining the target number based on the processing parameters of the examination service desk, so that the state transition information of the examination service desk during the examination of the patients can be obtained, and the state transition diagrams of the two examination service desks are constructed according to the state transition information. And based on the state transition diagram, constructing a balance equation when the examination service desk examines each patient in the examination request information flow, and analyzing the balance equation by adopting a matrix geometric solution method, thereby obtaining the steady-state probability of the examination service desk group examining a preset number of patients in a steady state.

The server classifies the steady-state probabilities according to the types of the processing queues to obtain target steady-state probabilities corresponding to the number of patients in each processing queue, then respectively calculates expected numbers of expected examination patients in the two processing queues according to the target steady-state probabilities, and the ratio of the expected numbers of the two processing queues can be used as segmentation information of the examination request information flow.

The server calculates first processing time required by the examination service desk for completing the examination of the patient corresponding to the examination request information flow according to the segmentation information, extracts target waiting time of all patients in the examination service desk group during examination in the first processing time, compares the target waiting time with a preset waiting time threshold, can determine that the segmentation information has no problem when the target waiting time does not exceed the preset waiting time threshold, can also obtain attribute information of the examination request information flow of the patient, determines the processing level of the examination request information flow of the patient according to the attribute information, and determines a maximum time for examining the patient as the target processing time according to the processing level. And the server calculates second processing time required by the examination service desk for completing the examination of the patient corresponding to the examination request information flow according to the segmentation information, compares the second processing time with the target processing time, and can determine that the segmentation information has no problem when the second processing time does not exceed the target processing time.

The server divides the examination request information flow of the arriving patient into two target information flows according to the division information, guides the patient in the target information flow to the corresponding queuing for queuing examination according to the divided target information flows, the examination service desk corresponding to the queuing queue examines the patient, and after the examination is finished, the patient can be prompted to go to the next examination service desk for examination, so that all examination items of the reserved patient are finished, specifically as shown in fig. 5.

In order to better implement the above method, an embodiment of the present invention further provides an information distribution processing apparatus, where the information distribution processing apparatus may be integrated in an electronic device, such as a server or a terminal, and the terminal may include a tablet computer, a notebook computer, and/or a personal computer.

For example, as shown in fig. 6, the information distribution processing apparatus may include an acquisition unit 301, a generation unit 302, a calculation unit 303, a determination unit 304, a division unit 305, and a processing unit 306, as follows:

(1) An acquisition unit 301;

an obtaining unit 301, configured to obtain a medical order information flow, transmission parameters of the medical order information flow, and current processing information of a medical device group, where the medical device group includes at least two medical devices and a processing queue corresponding to the medical devices, and the current processing information includes processing parameters of the medical devices for the medical order information in the processing queue.

For example, the obtaining unit 301 may be specifically configured to directly obtain the medical order information stream and the transmission parameter of the medical order information stream, obtain attribute information of the medical device group, and extract current processing information of the medical device when the medical device processes the medical order information stream from the attribute information.

(2) A generation unit 302;

a generating unit 302, configured to generate, according to the transmission parameter and the processing parameter, a state transition characteristic of the medical device group, where the state transition characteristic is used to instruct the medical device group to process state transition information of the medical order information stream.

For example, the generating unit 302 may be specifically configured to determine, according to the transmission parameter, that the target quantity of the medical order information in the medical order information flow within the preset time is based on the processing parameter, and simulate the medical equipment group to process the medical order information of the target quantity, so as to obtain state transition information of the medical equipment processing the medical order information; and performing feature extraction on the state transition information to obtain the state transition features of the medical equipment group, or determining the state information of each medical equipment processing medical order information flow in the medical equipment group according to the transmission parameters and the processing parameters, fusing the state information to obtain the state transition information of the medical equipment processing medical order information flow, and performing feature extraction on the state transition information to obtain the state transition features of the medical equipment group.

(3) A calculation unit 303;

a calculating unit 303, configured to calculate a steady-state probability of the medical device group processing the medical order information stream in the preset state based on the state transition feature, where the steady-state probability is used to indicate a probability of the medical device group processing a preset amount of medical order information,

for example, the calculating unit 303 may be specifically configured to determine, according to the state transition characteristic, processing balance information of the medical device group for processing the medical order information stream, analyze the processing balance information to obtain an initial steady-state probability of the medical device group for processing the medical order information stream in the preset state, and fuse the initial steady-state probabilities to obtain a steady-state probability of the medical device group for processing the medical order information stream in the preset state.

(4) A determination unit 304;

a determining unit 304 is configured to determine a segmentation parameter of the medical order information flow according to the steady-state probability.

For example, the determining unit 304 may be specifically configured to classify the steady-state probabilities according to the types of the processing queues to obtain target steady-state probabilities corresponding to the medical order information quantities in the processing queues, calculate target processing quantities of each processing queue within a preset time based on the target steady-state probabilities, and determine the segmentation parameters of the medical order information flows according to the target processing quantities.

(5) A dividing unit 305;

a segmentation unit 305, configured to segment the medical order information flow based on the segmentation parameters, so as to obtain a target medical order information flow corresponding to the processing queue.

For example, the segmenting unit 305 may be specifically configured to mark the medical order information streams according to the segmentation parameters and the arrival time of the medical order information, mark the corresponding processing queues respectively, and segment the marked medical order information streams to obtain the target medical order information streams corresponding to the processing queues.

(6) A processing unit 306;

the processing unit 306 is configured to send the target medical order information flow to the processing queue, so that the medical equipment group processes the target medical order information flow.

For example, the processing unit 306 may be specifically configured to send the segmented target medical order information stream to a corresponding processing queue, where the medical device processes the medical order information in the processing queue corresponding to the medical device according to a preset processing path, sends the medical order information in the processed target medical order information stream to a next medical device according to the preset processing path, and after receiving the medical order information, the next medical device processes the medical order information according to the processing parameter corresponding to the processing queue in which the medical order information is located, and after the processing is completed, continues to send the medical order information to the next medical device until each medical device in the medical device group completes processing the medical order information.

In specific implementation, the above units may be implemented as independent entities, or may be combined arbitrarily, and implemented as the same or several entities, and specific implementations of the above units may refer to the foregoing method embodiment, which is not described herein again.

As can be seen from the above, in this embodiment, after the obtaining unit 301 obtains a medical order information flow, a transmission parameter of the medical order information flow, and current processing information of a medical device group, the medical device group includes at least two medical devices and a processing queue corresponding to the medical devices, and the current processing information includes a processing parameter of the medical device for the medical order information in the processing queue, then, the generating unit 302 generates a state transition feature of the medical device group according to the transmission parameter and the processing parameter, where the state transition feature is used to indicate the medical device group to process the state transition information of the medical order information flow, then, the calculating unit 303 calculates a steady state probability of the medical device group processing the medical order information flow in a preset state based on the state transition feature, where the steady state probability is used to indicate a probability of the medical device group processing a preset number of medical order information, then, the determining unit 304 determines a segmentation parameter of the medical order information flow according to the steady state probability, the segmenting unit 305 segments the medical order information flow based on the segmentation parameter, obtains a target medical order information flow corresponding to the processing queue, and the processing unit 306 sends the target medical order information flow to the processing queue so that the target medical device group processes the target medical order information flow; according to the scheme, the state transition characteristics of the medical equipment group are generated according to the transmission parameters and the processing parameters, the steady-state probability of processing the medical order information is calculated, then the medical order information flow is segmented according to the steady-state probability, the internal state of the medical equipment group is fully considered, the medical order information distribution is more balanced, and therefore the information processing efficiency can be greatly improved.

An embodiment of the present invention further provides an electronic device, as shown in fig. 7, which shows a schematic structural diagram of the electronic device according to the embodiment of the present invention, specifically:

the electronic device may include components such as a processor 401 of one or more processing cores, memory 402 of one or more computer-readable storage media, a power supply 403, and an input unit 404. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 7 does not constitute a limitation of the electronic device and may include more or fewer components than shown, or some components may be combined, or a different arrangement of components. Wherein:

the processor 401 is a control center of the electronic device, connects various parts of the whole electronic device by various interfaces and lines, performs various functions of the electronic device and processes data by running or executing software programs and/or modules stored in the memory 402 and calling data stored in the memory 402, thereby performing overall monitoring of the electronic device. Alternatively, processor 401 may include one or more processing cores; preferably, the processor 401 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 401.

The memory 402 may be used to store software programs and modules, and the processor 401 executes various functional applications and data processing by operating the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data created according to use of the electronic device, and the like. Further, the memory 402 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. Accordingly, the memory 402 may also include a memory controller to provide the processor 401 access to the memory 402.

The electronic device further comprises a power supply 403 for supplying power to the various components, and preferably, the power supply 403 is logically connected to the processor 401 through a power management system, so that functions of managing charging, discharging, and power consumption are realized through the power management system. The power supply 403 may also include any component of one or more dc or ac power sources, recharging systems, power failure detection circuitry, power converters or inverters, power status indicators, and the like.

The electronic device may further include an input unit 404, and the input unit 404 may be used to receive input numeric or character information and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

Although not shown, the electronic device may further include a display unit and the like, which are not described in detail herein. Specifically, in this embodiment, the processor 401 in the electronic device loads the executable file corresponding to the process of one or more application programs into the memory 402 according to the following instructions, and the processor 401 runs the application program stored in the memory 402, thereby implementing various functions as follows:

For example, the electronic device may directly obtain the medical order information stream and the transmission parameters of the medical order information stream, obtain attribute information of the medical device group, and extract current processing information of the medical device when processing the medical order information stream from the attribute information. According to the transmission parameters, determining the target quantity of the medical order information in the medical order information flow in the preset time, and simulating the medical order information of the medical equipment group to process the target quantity based on the processing parameters to obtain the state transition information of the medical order information processed by the medical equipment; and performing feature extraction on the state transition information to obtain the state transition features of the medical equipment group, or determining the state information of each medical equipment processing medical order information flow in the medical equipment group according to the transmission parameters and the processing parameters, fusing the state information to obtain the state transition information of the medical equipment processing medical order information flow, and performing feature extraction on the state transition information to obtain the state transition features of the medical equipment group. According to the state transition characteristics, processing balance information of the medical order information flow processed by the medical equipment group is determined, the processing balance information is analyzed, initial steady-state probability of the medical order information flow processed by the medical equipment group in the preset state is obtained, the initial steady-state probability is fused, and the steady-state probability of the medical order information flow processed by the medical equipment group in the preset state is obtained. And classifying the steady-state probabilities according to the types of the processing queues to obtain target steady-state probabilities corresponding to the medical order information quantities in the processing queues, calculating the target processing quantities of each processing queue in preset time based on the target steady-state probabilities, and determining the segmentation parameters of the medical order information streams according to the target processing quantities. Marking the medical order information flow according to the segmentation parameters and the arrival time of the medical order information, respectively marking a corresponding processing queue, and segmenting the marked medical order information flow to obtain a target medical order information flow corresponding to the processing queue. The segmented target medical order information flow is sent to a corresponding processing queue, the medical equipment processes the medical order information in the processing queue corresponding to the medical equipment according to a preset processing path, the medical order information in the processed target medical order information flow is sent to the next medical equipment according to the preset processing path, the next medical equipment processes the medical order information according to the processing parameters corresponding to the processing queue where the medical order information is located after receiving the medical order information, and after the processing is finished, the medical order information continues to be sent to the next medical equipment until each medical equipment in the medical equipment group completes the processing of the medical order information.

The above operations can be implemented in the foregoing embodiments, and are not described herein.

As can be seen from the above, after acquiring a medical order information stream, transmission parameters of the medical order information stream, and current processing information of a medical device group, the medical device group includes at least two medical devices and a processing queue corresponding to the medical devices, the current processing information includes processing parameters of the medical devices for the medical order information in the processing queue, then, according to the transmission parameters and the processing parameters, a state transition characteristic of the medical device group is generated, the state transition characteristic is used to indicate the medical device group to process state transition information of the medical order information stream, then, based on the state transition characteristic, a steady state probability of the medical device group processing the medical order information stream in a preset state is calculated, the steady state probability is used to indicate a probability of the medical device group processing a preset number of pieces of medical order information, then, according to the steady state probability, a segmentation parameter of the medical order information stream is determined, the medical order information stream is segmented based on the segmentation parameter, a target medical order information stream corresponding to the processing queue is obtained, and the target medical order information stream is sent to the processing queue, so that the medical device group processes the target order information stream; according to the scheme, the state transition characteristics of the medical equipment group are generated according to the transmission parameters and the processing parameters, the steady-state probability of processing the medical order information is calculated, then the medical order information flow is segmented according to the steady-state probability, the internal state of the medical equipment group is fully considered, the medical order information distribution is more balanced, and therefore the information processing efficiency can be greatly improved.

It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by associated hardware controlled by the instructions, which may be stored in a computer readable storage medium and loaded and executed by a processor.

To this end, the embodiment of the present invention provides a computer-readable storage medium, in which a plurality of instructions are stored, where the instructions can be loaded by a processor to execute the steps in any information distribution processing method provided by the embodiment of the present invention. For example, the instructions may perform the steps of:

the method comprises the steps of obtaining a medical order information flow, transmission parameters of the medical order information flow and current processing information of a medical equipment group, wherein the medical equipment group comprises at least two medical equipment and processing queues corresponding to the medical equipment, the current processing information comprises processing parameters of the medical equipment aiming at the medical order information in the processing queues, state transition characteristics of the medical equipment group are generated according to the transmission parameters and the processing parameters, the state transition characteristics are used for indicating the state transition information of the medical equipment group for processing the medical order information flow, the steady-state probability of the medical equipment group for processing the medical order information flow in the preset state is calculated based on the state transition characteristics, the steady-state probability is used for indicating the probability of the medical equipment group for processing the preset number of medical order information, the segmentation parameters of the medical order information flow are determined according to the steady-state probability, the medical order information flow is segmented based on the segmentation parameters, the target medical order information flow corresponding to the processing queues is obtained, and the target medical order information flow is sent to the processing queues so that the medical equipment group processes the target medical order information flow.

For example, the electronic device may directly obtain the medical order information stream and the transmission parameters of the medical order information stream, obtain attribute information of the medical device group, and extract current processing information of the medical device when processing the medical order information stream from the attribute information. According to the transmission parameters, determining the target quantity of the medical order information in the medical order information flow within the preset time, and simulating the medical order information of the medical equipment group for processing the target quantity based on the processing parameters to obtain the state transition information of the medical equipment for processing the medical order information; and performing feature extraction on the state transition information to obtain the state transition features of the medical equipment group, or determining the state information of each medical equipment processing medical order information flow in the medical equipment group according to the transmission parameters and the processing parameters, fusing the state information to obtain the state transition information of the medical equipment processing medical order information flow, and performing feature extraction on the state transition information to obtain the state transition features of the medical equipment group. According to the state transition characteristics, processing balance information of the medical order information flow processed by the medical equipment group is determined, the processing balance information is analyzed, initial steady-state probability of the medical order information flow processed by the medical equipment group in the preset state is obtained, the initial steady-state probability is fused, and the steady-state probability of the medical order information flow processed by the medical equipment group in the preset state is obtained. And classifying the steady-state probabilities according to the types of the processing queues to obtain target steady-state probabilities corresponding to the medical order information quantities in the processing queues, calculating the target processing quantities of each processing queue in preset time based on the target steady-state probabilities, and determining the segmentation parameters of the medical order information flows according to the target processing quantities. Marking the medical order information flow according to the segmentation parameters and the arrival time of the medical order information, respectively marking a corresponding processing queue, and segmenting the marked medical order information flow to obtain a target medical order information flow corresponding to the processing queue. The segmented target medical order information flow is sent to a corresponding processing queue, the medical equipment processes the medical order information in the processing queue corresponding to the medical equipment according to a preset processing path, the medical order information in the processed target medical order information flow is sent to the next medical equipment according to the preset processing path, the next medical equipment processes the medical order information according to the processing parameters corresponding to the processing queue where the medical order information is located after receiving the medical order information, and the medical order information is continuously sent to the next medical equipment after the processing is finished until each medical equipment in the medical equipment group finishes the processing of the medical order information.

The above operations can be implemented in the foregoing embodiments, and are not described in detail herein.

Wherein the computer-readable storage medium may include: read Only Memory (ROM), random Access Memory (RAM), magnetic or optical disks, and the like.

Since the instructions stored in the computer-readable storage medium can execute the steps in any information offloading processing method provided in the embodiment of the present invention, beneficial effects that can be achieved by any information offloading processing method provided in the embodiment of the present invention can be achieved, for details, see the foregoing embodiments, and are not described herein again.

According to an aspect of the application, there is provided, among other things, a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The computer instructions are read by a processor of the computer device from a computer-readable storage medium, and the computer instructions are executed by the processor to cause the computer device to perform the methods provided in the various alternative implementations of the information processing aspect described above.

The information distribution processing method, apparatus, and computer-readable storage medium provided in the embodiments of the present invention are described in detail above, and specific examples are applied in this document to explain the principles and implementations of the present invention, and the descriptions of the above embodiments are only used to help understanding the method and its core ideas of the present invention; meanwhile, for those skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed, and in summary, the content of the present specification should not be construed as limiting the present invention.

Claims

1. An information distribution processing method is characterized by comprising the following steps:

generating a state transition characteristic of the medical equipment group according to the transmission parameter and the processing parameter, wherein the state transition characteristic is used for indicating the medical equipment group to process state transition information of a medical order information flow, and the generating the state transition characteristic of the medical equipment group according to the transmission parameter and the processing parameter comprises: determining the target quantity of the medical order information in the medical order information flow within a preset time according to the transmission parameters; simulating the medical order information of the target quantity processed by the medical equipment group based on the processing parameters to obtain the state transition information of the medical order information processed by the medical equipment; performing feature extraction on the state transition information to obtain state transition features of the medical equipment group; or, the generating the state transition characteristics of the medical device group according to the transmission parameters and the processing parameters includes: determining the state information of each medical device in the medical device group for processing the medical order information flow according to the transmission parameters and the processing parameters; fusing the state information to obtain state transition information of the medical equipment for processing the medical order information flow; performing feature extraction on the state transition information to obtain state transition features of the medical equipment group; the state transition feature comprises a state transition diagram for the group of medical devices;

based on the state transition characteristics, calculating a steady-state probability of the medical equipment group processing the medical order information flow in a preset state, where the steady-state probability is used to indicate a probability of the medical equipment group processing a preset number of pieces of medical order information, and based on the state transition characteristics, calculating a steady-state probability of the medical equipment group processing the medical order information flow in a preset state, including: determining processing balance information of the medical order information flow processed by the medical equipment group according to the state transition characteristics, wherein the processing balance information indicates a processing balance relationship of each piece of medical order information in the medical order information flow processed by the medical equipment; analyzing the processing balance information to obtain the initial steady-state probability of the medical equipment group for processing each piece of medical order information; fusing the initial steady-state probabilities to obtain the steady-state probabilities of the medical equipment group for processing the medical order information streams in a preset state;

determining the segmentation parameters of the medical order information flow according to the steady-state probability, wherein the determining the segmentation parameters of the medical order information flow according to the steady-state probability comprises the following steps: classifying the steady-state probabilities according to the types of the processing queues to obtain target steady-state probabilities corresponding to the quantity of the medical order information in the processing queues; calculating the target processing quantity of each processing queue in preset time based on the target steady-state probability; determining segmentation parameters of the medical order information flow according to the target processing quantity; or respectively calculating the ratio of the target processing quantities of the processing queue according to the target processing quantities to obtain the initial segmentation parameters of the medical order information flow; fusing the initial segmentation parameters to obtain segmentation information of the medical order information flow; identifying a segmentation parameter corresponding to the processing queue in the segmentation information;

dividing the medical order information flow based on the dividing parameters to obtain a target medical order information flow corresponding to the processing queue;

sending the target medical order information flow to the processing queue so that the medical equipment group can process the target medical order information flow;

determining processing balance information of the medical order information flow processed by the medical equipment group according to the state transition characteristics, analyzing the processing balance information, and obtaining an initial steady-state probability of the medical order information flow processed by the medical equipment group in a preset state, wherein the method comprises the following steps of:

according to the state transition diagram of the medical equipment group, a balance equation between the arrival and the processing end of each piece of medical order information is constructed, and the initial steady-state probability in the balance equation is solved, wherein the balance equation is as follows:

…

wherein,

is the arrival rate of the medical order information,

to handle the arrival rate of queue 1,

to handle the arrival rate of queue 2,

the capacity of the medical device a is allocated a proportion to the capacity of the two processing queues,

the capacity of the medical device B is allocated according to the proportion of the capacity of the two processing queues,

the processing rate for processing the medical order information for medical device A is processing queue 1 at a processing rate of

The arrival rate of processing queue 2 is

，

A processing rate of processing the medical order information for the medical device B, the processing rate of the processing queue 1 being

The arrival rate of the processing queue 2 is

，

Is the steady state probability that the number of medical order information in the system of processing queue 1 is i, and the number of medical order information in the system of processing queue 2 is j in the current system.

2. The information distribution processing method according to claim 1, wherein after the fusing the initial segmentation parameters to obtain the segmentation information of the medical order information stream, the method further includes:

calculating first processing time for processing the medical order information flow by the medical equipment group according to the segmentation information;

extracting target waiting time of the medical order information in the medical equipment group from the first processing time;

the identifying, in the segmentation information, the segmentation parameter corresponding to the processing queue includes: and when the target waiting time does not exceed a preset waiting time threshold, identifying a segmentation parameter corresponding to the processing queue in the segmentation information.

3. The information distribution processing method according to claim 2, wherein after the fusing the initial segmentation parameters to obtain the segmentation information of the medical order information stream, the method further comprises:

acquiring attribute information of the medical order information flow, and determining the processing level of the medical order information flow according to the attribute information;

determining target processing time of the medical order information flow according to the processing grade;

calculating a second processing time for the medical device group to process the medical order information stream based on the segmentation information;

the identifying, in the segmentation information, the segmentation parameter corresponding to the processing queue includes: when the second processing time does not exceed the target processing time, identifying a partition parameter corresponding to the processing queue in the partition information.

4. An information distribution processing apparatus, comprising:

a generating unit, configured to generate a state transition feature of the medical device group according to the transmission parameter and the processing parameter, where the state transition feature is used to instruct the medical device group to process state transition information of a medical order information flow, and the generating of the state transition feature of the medical device group according to the transmission parameter and the processing parameter includes: determining the target quantity of the medical order information in the medical order information flow within a preset time according to the transmission parameters; simulating the medical equipment group to process the medical order information of the target quantity based on the processing parameters to obtain state transition information of the medical equipment for processing the medical order information; performing feature extraction on the state transition information to obtain state transition features of the medical equipment group; or, the generating the state transition characteristics of the medical device group according to the transmission parameters and the processing parameters includes: determining the state information of each medical device in the medical device group for processing the medical order information flow according to the transmission parameters and the processing parameters; fusing the state information to obtain state transition information of the medical equipment for processing the medical order information flow; performing feature extraction on the state transition information to obtain state transition features of the medical equipment group; the state transition feature comprises a state transition diagram for the group of medical devices;

the calculating unit is configured to calculate a steady-state probability of the medical device group processing the medical order information flow in a preset state based on the state transition feature, where the steady-state probability is used to indicate a probability of the medical device group processing a preset number of pieces of medical order information, and the calculating unit is configured to calculate the steady-state probability of the medical device group processing the medical order information flow in the preset state based on the state transition feature, and includes: determining processing balance information of the medical equipment group for processing the medical order information flow according to the state transition characteristics, wherein the processing balance information indicates a processing balance relationship of the medical equipment for processing each piece of medical order information in the medical order information flow; analyzing the processing balance information to obtain the initial steady-state probability of the medical equipment group for processing each piece of medical order information; fusing the initial steady-state probabilities to obtain the steady-state probabilities of the medical equipment group for processing the medical order information streams in a preset state;

the determining unit is configured to determine the segmentation parameter of the medical order information flow according to the steady-state probability, and the determining the segmentation parameter of the medical order information flow according to the steady-state probability includes: classifying the steady-state probability according to the type of the processing queue to obtain a target steady-state probability corresponding to the quantity of the medical order information in the processing queue; calculating the target processing quantity of each processing queue in preset time based on the target steady-state probability; determining segmentation parameters of the medical order information flow according to the target processing quantity; or respectively calculating the ratio of the target processing quantities of the processing queue according to the target processing quantities to obtain the initial segmentation parameters of the medical order information flow; fusing the initial segmentation parameters to obtain segmentation information of the medical order information flow; identifying a segmentation parameter corresponding to the processing queue in the segmentation information;

the processing unit is used for sending the target medical order information flow to the processing queue so that the medical equipment group can process the target medical order information flow;

according to the state transition diagram of the medical equipment group, a balance equation between the arrival of each piece of medical order information and the end of processing is constructed, and the initial steady-state probability in the balance equation is solved, wherein the balance equation is as follows:

…

wherein,

is the arrival rate of the medical order information,

to handle the arrival rate of queue 1,

in order to handle the arrival rate of queue 2,

the capacity of the medical equipment A is allocated to a proportion of the capacity of the two treatment queues,

the capacity of the medical equipment B is allocated according to the proportion of the capacity of the two processing queues,

The arrival rate of processing queue 2 is

，

The arrival rate of the processing queue 2 is

，

5. A computer-readable storage medium, wherein the computer-readable storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor to execute the steps in the information distribution processing method according to any one of claims 1 to 3.