CN112714020B - Method and device for determining validity of data, storage medium and electronic device - Google Patents
Method and device for determining validity of data, storage medium and electronic device Download PDFInfo
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- CN112714020B CN112714020B CN202011589543.3A CN202011589543A CN112714020B CN 112714020 B CN112714020 B CN 112714020B CN 202011589543 A CN202011589543 A CN 202011589543A CN 112714020 B CN112714020 B CN 112714020B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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- H04L43/10—Active monitoring, e.g. heartbeat, ping or trace-route
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Abstract
The invention provides a method and a device for determining data validity, a storage medium and an electronic device, wherein the method comprises the following steps: determining the confidence coefficient of the state data of the target equipment at the current time according to the confidence coefficient of the state data of the target equipment at the first time, wherein the first time is the time of determining the confidence coefficient of the state data at the last time before the current time; and determining that the state data is valid when the confidence of the state data at the current time is in a target confidence interval. The invention solves the technical problem that whether the equipment state data is valid or not can not be determined in the related technology, and can determine the validity of the equipment state data.
Description
Technical Field
The invention relates to the technical field of Internet of things, in particular to a method and a device for determining data validity, a storage medium and an electronic device.
Background
At present, an Internet of Things (IoT) platform in the industry stores data of state data of IoT devices connected to the IoT platform, but when the state data of the IoT platform is used, validity of the data is not judged, and it cannot be guaranteed that the state data stored by the current IoT platform is consistent with actual state data of the current devices.
Aiming at the technical problem that whether the equipment state data is effective or not cannot be determined in the related technology, an effective technical scheme is not provided.
Disclosure of Invention
The embodiment of the invention provides a method and a device for determining data validity, a storage medium and an electronic device, which are used for at least solving the technical problem that whether equipment state data are valid cannot be determined in the related art.
According to an embodiment of the present invention, there is provided a method for determining validity of data, including: determining the confidence level of the state data at the current time according to the confidence level of the state data of the target device at the first time, wherein the first time is the time of determining the confidence level of the state data at the last time before the current time; and determining that the state data is valid when the confidence of the state data at the current time is in a target confidence interval.
In an exemplary embodiment, the determining the confidence level of the state data of the target device at the current time according to the confidence level of the state data of the target device at the first time includes: determining a confidence coefficient corresponding to the target device and a time difference between the current time and the first time; and determining the confidence of the state data at the current time according to the confidence of the state data at the first time, the confidence attenuation coefficient and the time difference.
In an exemplary embodiment, said determining the confidence level of the state data at the current time based on the confidence level of the state data at the first time, the confidence level attenuation factor, and the time difference comprises: determining a confidence f of the state data at the current time according to the following formula t ：
f t =f′×e -a×△t ,
Wherein f' is the confidence of the state data at the first time, a is the confidence attenuation coefficient, and Δ t is the time difference.
In one exemplary embodiment, the method further comprises: correspondingly storing the state data and the confidence of the state data at the current time; and under the condition that the state data are effective, managing the target equipment according to the state data.
In one exemplary embodiment, after the determining that the status data is valid, the method further comprises: and under the condition of acquiring the behavior information of the target equipment, correcting the confidence corresponding to the state data according to the behavior information, and correspondingly storing the corrected confidence and the state data.
In an exemplary embodiment, the modifying the confidence corresponding to the state data according to the behavior information when the behavior information of the target device is obtained includes: under the condition that the behavior information is the state data reported by the target equipment, correcting the confidence coefficient corresponding to the state data into a preset initial confidence coefficient; increasing a first numerical value to the confidence degree corresponding to the state data under the condition that the behavior information is heartbeat information sent by the target equipment; and subtracting a second numerical value from the confidence corresponding to the state data when the behavior information is that the target device is detected to be offline.
In an exemplary embodiment, before the increasing the confidence level corresponding to the state data by the first value, the method further includes: determining the first value δ according to the following equation:
wherein f is 0 And the initial confidence coefficient is defined as p, the half-life period of the confidence coefficient corresponding to the state data is defined as p, and the preset fixed confidence coefficient is defined as F.
According to another embodiment of the present invention, there is provided a data validity determination apparatus including: the device comprises a first determining module, a second determining module and a third determining module, wherein the first determining module is used for determining the confidence level of the state data at the current time according to the confidence level of the state data of the target device at the first time, and the first time is the time of determining the confidence level of the state data at the latest time before the current time; a second determining module, configured to determine that the state data is valid when the confidence of the state data at the current time is in a target confidence interval.
In an exemplary embodiment, the first determining module is further configured to: determining a confidence coefficient corresponding to the target device and a time difference between the current time and the first time; and determining the confidence of the state data at the current time according to the confidence of the state data at the first time, the confidence attenuation coefficient and the time difference.
In an exemplary embodiment, the first determining module is further configured to: determining a confidence f of the state data at the current time according to the following formula t ：
f t ＝f′×e -a×Δt ,
Wherein f' is the confidence of the state data at the first time, a is the confidence attenuation coefficient, and Δ t is the time difference.
In an exemplary embodiment, the apparatus further comprises: the storage module is used for correspondingly storing the state data and the confidence of the state data at the current time; and the management module is used for managing the target equipment according to the state data under the condition that the state data is effective.
In an exemplary embodiment, the apparatus further includes: and the correcting module is used for correcting the confidence corresponding to the state data according to the behavior information under the condition of acquiring the behavior information of the target equipment, and correspondingly storing the corrected confidence and the state data.
In an exemplary embodiment, the modification module is further configured to: under the condition that the behavior information is state data reported by the target equipment, correcting a confidence coefficient corresponding to the state data into a preset initial confidence coefficient; under the condition that the behavior information is heartbeat information sent by the target equipment, increasing a first numerical value to the confidence degree corresponding to the state data; and subtracting a second numerical value from the confidence corresponding to the state data when the behavior information is that the target device is detected to be offline.
In an exemplary embodiment, the modification module is further configured to: determining the first value δ according to the following equation:
wherein f is 0 And the initial confidence coefficient is defined as p, the half-life period of the confidence coefficient corresponding to the state data is defined as p, and the preset fixed confidence coefficient is defined as F.
According to another embodiment of the invention, a storage medium is provided, in which a computer program is stored, wherein the computer program is arranged to perform the above-mentioned method when executed.
According to another embodiment of the present invention, there is provided an electronic apparatus including a memory having a computer program stored therein and a processor configured to execute the computer program to perform the above method.
According to the method and the device, the confidence coefficient of the state data at the current time is determined according to the confidence coefficient of the state data of the target device at the first time, wherein the first time is the time of determining the confidence coefficient of the state data at the latest time before the current time; and determining that the state data is valid when the confidence of the state data at the current time is in a target confidence interval. The confidence degree of the state data of the target equipment can be determined, and whether the state data is valid or not can be determined according to the confidence degree of the state data, so that the validity of the state data of the target equipment can be determined, the technical problem that whether the equipment state data is valid or not cannot be determined in the related technology is solved, the validity of the state data of the equipment can be determined, and the invalid equipment state data is prevented from being used.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention and do not constitute a limitation of the invention. In the drawings:
fig. 1 is a block diagram of a hardware configuration of a mobile terminal of an embodiment of the present invention;
FIG. 2 is a flow chart of a method of determining data validity according to an embodiment of the present invention;
FIG. 3 is a flow chart of a method for determining validity of data according to an alternative embodiment of the present invention;
FIG. 4 is a flow chart of a method for determining validity of data according to an alternative embodiment of the present invention;
FIG. 5 is a flow chart of a method for determining validity of data according to an alternative embodiment of the present invention;
FIG. 6 is a flow chart of a method for determining validity of data according to an alternative embodiment of the present Invention (IV);
FIG. 7 is a graph of confidence decay, according to an alternative embodiment of the present invention;
fig. 8 is a block diagram of the structure of an intelligent device according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
Example 1
The method provided by the first embodiment of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Taking a mobile terminal as an example, fig. 1 is a hardware structure block diagram of the mobile terminal according to the embodiment of the present invention, and as shown in fig. 1, the mobile terminal may include one or more processors 102 (only one is shown in fig. 1) (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA, etc.), and a memory 104 for storing data, and optionally, the mobile terminal may further include a transmission device 106 for communication function and an input/output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration, and does not limit the structure of the mobile terminal. For example, the mobile terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
The memory 104 may be used to store computer programs, for example, software programs and modules of application software, such as computer programs corresponding to the data validity determination method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, so as to implement the above-mentioned method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the mobile terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a Network adapter (NIC) that can be connected to other Network devices through a base station to communicate with the internet. In one example, the transmitting device 106 may be a Radio FrequeNcy (RF) module, which is used to communicate with the internet via wireless.
Based on the foregoing mobile terminal or network architecture, in this embodiment, a method for determining data validity is provided, which is applied to an intelligent device, fig. 2 is a flowchart of a method for determining data validity according to an embodiment of the present invention, and as shown in fig. 2, the flowchart includes the following steps:
step S202, determining the confidence coefficient of the state data at the current time according to the confidence coefficient of the state data of the target equipment at the first time, wherein the first time is the time of determining the confidence coefficient of the state data at the latest time before the current time;
step S204, determining that the state data is valid under the condition that the confidence of the state data at the current time is in a target confidence interval.
Through the steps S202 to S204, determining the confidence level of the state data at the current time according to the confidence level of the state data of the target device at the first time, where the first time is the time when the confidence level of the state data is determined last before the current time; and determining that the state data is valid when the confidence of the state data at the current time is in a target confidence interval. The confidence degree of the state data of the target equipment can be determined, and whether the state data is valid or not can be determined according to the confidence degree of the state data, so that the validity of the state data of the target equipment can be determined, the technical problem that whether the equipment state data is valid or not cannot be determined in the related technology is solved, the validity of the state data of the equipment can be determined, and the invalid equipment state data is prevented from being used.
It should be noted that, in the above embodiment, the confidence of the state data may be determined in real time.
Fig. 3 is a flowchart illustrating a method for determining data validity according to an alternative embodiment of the present invention (i), as shown in fig. 3, the step S202 includes:
step S302, determining a confidence coefficient corresponding to the target device and a time difference between the current time and the first time;
step S304, determining the confidence of the state data at the current time according to the confidence of the state data at the first time, the confidence attenuation coefficient, and the time difference.
In the above embodiment, determining the confidence level of the state data at the current time requires determining the confidence level attenuation coefficient corresponding to the target device and the time difference, and then determining the confidence level at the current time according to the confidence level at the first time, the confidence level attenuation coefficient, and the time difference. Optionally, the confidence coefficient attenuation coefficient corresponding to the target device may be a confidence coefficient set for the target device according to the historical behavior information of the target device.
In an alternative embodiment, the step S304 includes: determining a confidence f for the state data at the current time according to the following formula t ：
f t ＝f′×e -a×Δt ,
Wherein f' is the confidence of the state data at the first time, a is the confidence attenuation coefficient, and Δ t is the time difference.
Fig. 4 is a schematic flow chart (ii) of a method for determining data validity according to an alternative embodiment of the present invention, and as shown in fig. 4, the method further includes:
step S402, correspondingly storing the state data and the confidence of the state data at the current time;
step S404, under the condition that the state data is valid, the target device is managed according to the state data.
In the above embodiment, the state data may be stored corresponding to the confidence of the state data at the current time, and the target device may be managed under the condition that the state data is valid, including but not limited to maintaining the target device using the state data, sending a control command to the target device according to the state data, and the like.
Fig. 5 is a schematic flow chart (iii) of a method for determining data validity according to an alternative embodiment of the present invention, and as shown in fig. 5, after the step S404, the method further includes:
step S502, under the condition that the behavior information of the target device is obtained, the confidence corresponding to the state data is corrected according to the behavior information, and the corrected confidence and the state data are correspondingly stored.
Based on the embodiment, the confidence of the state data can be corrected according to the behavior information of the device, and the corrected confidence and the state data are correspondingly stored, so that the confidence of the state data of the target device can be adjusted according to the actual behavior information of the target device.
Fig. 6 is a flowchart illustrating a method for determining data validity according to an alternative embodiment of the present invention (four), as shown in fig. 6, the step S502 includes:
step S602, in the case that the behavior information is the state data reported by the target device, correcting the confidence corresponding to the state data to a preset initial confidence;
step S604, increasing a first numerical value to the confidence corresponding to the state data under the condition that the behavior information is heartbeat information sent by the target device;
step S606, subtracting a second value from the confidence corresponding to the state data when the behavior information is that the target device is detected to be offline.
It should be noted that, in the above embodiment, the confidence of the state data is modified in different manners according to different behavior information of the target device.
In an optional embodiment, before the step S504, the method further includes: determining the first value δ according to the following equation:
wherein f is 0 And the initial confidence coefficient is defined as p, the half-life period of the confidence coefficient corresponding to the state data is defined as p, and the preset fixed confidence coefficient is defined as F. Optionally, the half-life is a confidence coefficient corresponding to the target device, and the confidence of the state data is set from f 0 Attenuation of 0.5 x f 0 The length of time elapsed. FIG. 7 is a graph of confidence decay, according to an alternative embodiment of the present invention.
The following explains the method for determining data validity in the above embodiment with reference to an example, but is not intended to limit the technical solution of the embodiment of the present invention.
In an optional embodiment, a method for determining data validity applied in the internet of things is provided, and the method includes the following steps:
and S1, state data reported by the cloud service storage equipment.
Step 2, the cloud service adds a confidence index (i.e. the confidence in the above embodiment) to the status data reported by each device; wherein, the confidence index is generated by real-time calculation based on the following functions:
current confidence index = last calculated confidence index x exp (- (confidence attenuation coefficient a) interval duration Δ t);
the interval duration Δ t is a time difference between the current time and the time when the confidence index of the state data is calculated for the last time. In an alternative embodiment, a decay curve for the confidence index of the simulated division is shown in FIG. 7.
It should be noted that, if there is no confidence index calculated last time, that is, the confidence index is calculated for the state data for the first time, the current confidence index is the preset initial confidence f 0 (including but not limited to 100); optionally, the confidence coefficient attenuation coefficient may be adjusted in real time according to the behavior information of the device;
and S3, after the current confidence index is calculated, storing the current confidence index.
As an alternative implementation manner, the foregoing embodiment is further configured to perform the following steps:
step S4, if the behavior information of the device is obtained, the confidence index corresponding to the state data is corrected according to the behavior information of the device and then stored, which includes but is not limited to:
the equipment reports state data: the confidence index corresponding to the reset state data is 100;
detecting a device heartbeat: confidence index increase (50/half-life) × 60 for status data;
detecting that the device is offline: the confidence index corresponding to the state data is reduced by 50.
Through the embodiment, the reliability index is corrected according to the actual behavior information of the equipment.
And S5, when the service side needs to use the stored equipment state data, judging according to the confidence index of the current state data.
And S6, for the state data in different confidence index intervals, the service side can be used differently according to different requirements of actual business on the accuracy of the data, and if the task data is not credible, the equipment side can directly inquire and update the state data.
Optionally, the service side may adjust the target confidence interval in the above embodiment as needed, so that effective state data may be obtained according to the updated target confidence interval.
Based on the embodiment, the confidence coefficient of each stored device state data can be dynamically calculated in real time, and the confidence coefficient of the device state data is automatically updated; meanwhile, the data can be selectively used by the business services with different data accuracy requirements according to the requirements of the business services, and the accuracy of the equipment state data stored in the service layer can be improved.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
Example 2
In this embodiment, a device for determining data validity is further provided, and fig. 8 is a block diagram of a structure of an intelligent device according to an embodiment of the present invention, as shown in fig. 8, including:
a first determining module 82, configured to determine a confidence level of the state data at a current time according to a confidence level of the state data of the target device at the first time, where the first time is a time at which the confidence level of the state data is determined last before the current time;
a second determining module 84, configured to determine that the state data is valid if the confidence of the state data at the current time is in a target confidence interval.
By the device, the confidence level of the state data at the current time is determined according to the confidence level of the state data of the target equipment at the first time, wherein the first time is the time of determining the confidence level of the state data at the latest time before the current time; and determining that the state data is valid when the confidence of the state data at the current time is in a target confidence interval. The confidence degree of the state data of the target device can be determined, and whether the state data is valid or not can be determined according to the confidence degree of the state data, so that the validity of the state data of the target device can be determined, the technical problem that whether the state data of the device is valid or not cannot be determined in the related technology is solved, the validity of the state data of the device can be determined, and the invalid state data of the device is prevented from being used.
In an optional embodiment, the first determining module is further configured to: determining a confidence coefficient attenuation coefficient corresponding to the target device and a time difference between the current time and the first time; and determining the confidence of the state data at the current time according to the confidence of the state data at the first time, the confidence attenuation coefficient and the time difference.
Determining the confidence of the state data at the current time requires determining a confidence attenuation coefficient and a time difference corresponding to the target device, and then determining the confidence of the current time according to the confidence of the first time, the confidence attenuation coefficient and the time difference.
In an optional embodiment, the first determining module is further configured to: determining a confidence f for the state data at the current time according to the following formula t ：
f t ＝f′×e -a×Δt ,
Wherein f' is the confidence of the state data at the first time, a is the confidence attenuation coefficient, and Δ t is the time difference.
In an optional embodiment, the apparatus further comprises: the storage module is used for correspondingly storing the state data and the confidence of the state data at the current time; and the management module is used for managing the target equipment according to the state data under the condition that the state data is effective.
In the above embodiment, the confidence of the state data at the current time may be stored correspondingly, and the target device may be managed according to the state data when the state data is valid.
In an optional embodiment, the apparatus further comprises: and the correcting module is used for correcting the confidence corresponding to the state data according to the behavior information under the condition of acquiring the behavior information of the target equipment, and correspondingly storing the corrected confidence and the state data.
Based on the above embodiment, the confidence of the state data of the device may also be corrected and stored according to the behavior information of the device.
In an optional embodiment, the modification module is further configured to: under the condition that the behavior information is state data reported by the target equipment, correcting a confidence coefficient corresponding to the state data into a preset initial confidence coefficient; increasing a first numerical value to the confidence degree corresponding to the state data under the condition that the behavior information is heartbeat information sent by the target equipment; and subtracting a second numerical value from the confidence corresponding to the state data when the behavior information is that the target device is detected to be offline.
By the embodiment, the confidence of the state data can be corrected in different modes according to different equipment behavior information.
In an optional embodiment, the modification module is further configured to: determining the first value δ according to the following equation:
wherein, f 0 And the initial confidence coefficient is defined as p, the half-life period of the confidence coefficient corresponding to the state data is defined as p, and the preset fixed confidence coefficient is defined as F.
Example 3
An embodiment of the present invention further provides a storage medium having a computer program stored therein, wherein the computer program is configured to perform the steps in any of the method embodiments described above when executed.
Alternatively, in the present embodiment, the storage medium may be configured to store a computer program for executing the steps of:
s1, determining the confidence coefficient of state data at the current time according to the confidence coefficient of the state data of target equipment at the first time, wherein the first time is the time of determining the confidence coefficient of the state data at the latest time before the current time;
s2, determining that the state data is valid under the condition that the confidence of the state data at the current time is in a target confidence interval.
Optionally, in this embodiment, the storage medium may include but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-ONly Memory (ROM), a RaNdom Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Example 4
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
s1, determining the confidence coefficient of state data at the current time according to the confidence coefficient of the state data of target equipment at the first time, wherein the first time is the time of determining the confidence coefficient of the state data at the latest time before the current time;
and S2, determining that the state data is valid under the condition that the confidence of the state data at the current time is in a target confidence interval.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and this embodiment is not described herein again.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A method for determining data validity, comprising:
determining the confidence level of the state data at the current time according to the confidence level of the state data of the target device at the first time, wherein the confidence level of the state data at the current time is determined last time before the current time, and the confidence level attenuation coefficient and the time difference of the state data at the current time are determined;
determining that the state data is valid when the confidence of the state data at the current time is in a target confidence interval;
correspondingly storing the state data and the confidence of the state data at the current time;
under the condition that the state data are effective, managing the target equipment according to the state data;
under the condition that the behavior information of the target equipment is obtained, the confidence corresponding to the state data is corrected according to the behavior information, and the corrected confidence and the state data are correspondingly stored;
in the case of acquiring the behavior information of the target device, modifying the confidence corresponding to the state data according to the behavior information includes:
under the condition that the behavior information is state data reported by the target equipment, correcting a confidence coefficient corresponding to the state data into a preset initial confidence coefficient;
under the condition that the behavior information is heartbeat information sent by the target equipment, increasing a first numerical value to the confidence degree corresponding to the state data;
and subtracting a second numerical value from the confidence corresponding to the state data under the condition that the behavior information is that the target device is detected to be offline.
2. The method of claim 1, wherein determining the confidence level of the state data at the current time based on the confidence level of the state data at the first time, the confidence level attenuation factor, and the time difference comprises:
determining a confidence f of the state data at the current time according to the following formula t ：
f t ＝f′×e -a×Δt ,
Wherein f' is the confidence of the state data at the first time, a is the confidence attenuation coefficient, and Δ t is the time difference.
3. The method of claim 1, wherein prior to said increasing the confidence level corresponding to the state data by the first value, the method further comprises:
determining the first value δ according to the following equation:
wherein, f 0 And the initial confidence coefficient is defined as p, the half-life period of the confidence coefficient corresponding to the state data is defined as p, and the preset fixed confidence coefficient is defined as F.
4. An apparatus for determining validity of data, comprising:
a first determining module, configured to determine a confidence level of state data of a target device at a current time according to a confidence level of the state data at the current time, where the confidence level of the state data is determined last before the current time, and the confidence level of the state data at the current time is determined according to a confidence level attenuation coefficient corresponding to the target device and a time difference between the current time and the first time;
the second determining module is used for determining that the state data is valid under the condition that the confidence coefficient of the state data at the current time is in a target confidence coefficient interval;
the storage module is used for correspondingly storing the state data and the confidence of the state data at the current time;
the management module is used for managing the target equipment according to the state data under the condition that the state data is effective;
the correcting module is used for correcting the confidence corresponding to the state data according to the behavior information under the condition that the behavior information of the target device is obtained, and correspondingly storing the corrected confidence and the state data; under the condition that the behavior information is state data reported by the target equipment, correcting a confidence coefficient corresponding to the state data into a preset initial confidence coefficient; increasing a first numerical value to the confidence degree corresponding to the state data under the condition that the behavior information is heartbeat information sent by the target equipment; and subtracting a second numerical value from the confidence corresponding to the state data when the behavior information is that the target device is detected to be offline.
5. A storage medium, in which a computer program is stored, wherein the computer program is arranged to perform the method of any of claims 1 to 3 when executed.
6. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method of any of claims 1 to 3 by means of the computer program.
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