CN117394945B - Method, device and equipment for detecting ports of optical splitters based on multivariate algorithm - Google Patents
Method, device and equipment for detecting ports of optical splitters based on multivariate algorithm Download PDFInfo
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- 230000003287 optical effect Effects 0.000 title claims abstract description 224
- 238000012627 multivariate algorithm Methods 0.000 title claims abstract description 48
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000004458 analytical method Methods 0.000 claims abstract description 43
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 28
- 238000012545 processing Methods 0.000 claims abstract description 9
- 238000001514 detection method Methods 0.000 claims description 28
- 238000004590 computer program Methods 0.000 claims description 27
- 239000000835 fiber Substances 0.000 claims description 23
- 238000011156 evaluation Methods 0.000 claims description 20
- 230000006870 function Effects 0.000 claims description 17
- 238000013468 resource allocation Methods 0.000 claims description 16
- 238000003066 decision tree Methods 0.000 claims description 14
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04J—MULTIPLEX COMMUNICATION
- H04J14/00—Optical multiplex systems
- H04J14/02—Wavelength-division multiplex systems
- H04J14/0201—Add-and-drop multiplexing
- H04J14/0202—Arrangements therefor
- H04J14/0204—Broadcast and select arrangements, e.g. with an optical splitter at the input before adding or dropping
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04J—MULTIPLEX COMMUNICATION
- H04J14/00—Optical multiplex systems
- H04J14/02—Wavelength-division multiplex systems
- H04J14/0227—Operation, administration, maintenance or provisioning [OAMP] of WDM networks, e.g. media access, routing or wavelength allocation
- H04J14/0254—Optical medium access
- H04J14/0272—Transmission of OAMP information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q11/00—Selecting arrangements for multiplex systems
- H04Q11/0001—Selecting arrangements for multiplex systems using optical switching
- H04Q11/0062—Network aspects
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q11/00—Selecting arrangements for multiplex systems
- H04Q11/0001—Selecting arrangements for multiplex systems using optical switching
- H04Q11/0062—Network aspects
- H04Q2011/0079—Operation or maintenance aspects
- H04Q2011/0083—Testing; Monitoring
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q11/00—Selecting arrangements for multiplex systems
- H04Q11/0001—Selecting arrangements for multiplex systems using optical switching
- H04Q11/0062—Network aspects
- H04Q2011/0086—Network resource allocation, dimensioning or optimisation
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Abstract
The application is applicable to the technical field of computers, and provides a method, a device and equipment for detecting a port of a beam splitter based on a multi-element algorithm, wherein the method for detecting the port of the beam splitter based on the multi-element algorithm comprises the following steps: acquiring service information of at least one optical splitter, wherein the service information comprises attribute information and port information shot by the at least one optical splitter within a preset duration; analyzing the attribute information and the port information based on at least one first preset analysis rule and at least one second preset analysis rule respectively to obtain a first resource occupation characteristic and a second resource occupation characteristic of each port of at least one optical splitter; and analyzing the first resource occupation characteristic and the second resource occupation characteristic by utilizing a predetermined multivariate algorithm to obtain the distribution accuracy of each port of at least one optical splitter. The scheme improves the efficiency and the quality of service processing.
Description
Technical Field
The application belongs to the technical field of computers, and particularly relates to a method, a device and equipment for detecting a port of a beam splitter based on a multivariate algorithm.
Background
Optical splitters, also known as optical splitters, are common network devices in various optical network rooms. The optical splitter is a fiber junction device having a plurality of input ends and a plurality of output ends, and is commonly used for accurately distributing optical resources.
Currently, the accuracy of optical resource allocation mainly depends on the accuracy of allocation of ports of an optical splitter. However, due to the passive characteristic of the optical splitter, when the ports of the optical splitter are mixed, an assembler cannot find out in time, so that the situation that the distribution result of the on-site ports of the optical splitter is inconsistent with the actually required port configuration occurs. Once the distribution result of the site ports is inconsistent with the actually required port configuration, serious influence is brought to operations such as new installation, disassembly, maintenance and the like, the efficiency and quality of service processing are greatly reduced, and the user experience is poor while the ever-increasing service demands cannot be met.
Disclosure of Invention
The embodiment of the application provides a method, a device and equipment for detecting a port of a beam splitter based on a multivariate algorithm, which can solve the problems.
In a first aspect, an embodiment of the present application provides a method for detecting a port of an optical splitter based on a multivariate algorithm, including: acquiring service information of at least one optical splitter, wherein the service information comprises attribute information and port information shot by the at least one optical splitter within a preset duration;
analyzing the attribute information and the port information based on at least one first preset analysis rule and at least one second preset analysis rule respectively to obtain a first resource occupation characteristic and a second resource occupation characteristic of each port of at least one optical splitter;
and analyzing the first resource occupation characteristic and the second resource occupation characteristic by utilizing a predetermined multivariate algorithm to obtain the distribution accuracy of each port of at least one optical splitter.
Further, the attribute information includes: type of beam splitter and identification information; port information, comprising: the port identification information, the port connection tail fiber information, the port occupation state and the port output optical signals.
Further, the first preset analysis rule includes:
and obtaining the first resource occupation characteristic of each port of at least one optical splitter according to the type of the optical splitter and/or the identification information of the optical splitter, the identification information of the port, the occupation state of the port and the optical signal output by the port.
Further, the second preset analysis rule includes:
determining an optical resource allocation task corresponding to the optical splitter according to the type of the optical splitter and/or the identification information of the optical splitter;
and determining the second resource occupation characteristic of each port of at least one optical splitter according to the optical resource allocation task, the tail fiber information of the port connection and the optical signals output by the ports.
Further, the first resource occupancy characteristic includes: the number of occupied ports of at least one optical splitter, the wavelength transmitted by each port and the specification attribute of the optical signal transmitted by each port; a second resource occupancy characteristic, comprising: the port of at least one optical splitter is connected with the correct rate of the second tail fiber information and the correct rate of the transmitted optical signal.
Further, the predetermined polynomial algorithm includes at least one polynomial algorithm selected from the following formulas (1) to (3):
Y=A×X，（1）
Y=X T ×A×X，（2）
Y=X T ×(X T ×A×X)，（3）
wherein Y is a target variable of a polynomial and is used for identifying the distribution accuracy of each port of at least one optical splitter, and X is a set of resource occupation characteristics of each port of at least one optical splitter, including a first resource occupation characteristic and a second resource occupation characteristic; a is an evaluation tensor of a preset dimension.
Further, the at least one polynomial algorithm comprises at least one decision tree function; the at least one decision tree function comprises at least one decision branch for deciding a target variable using the set of resource occupancy characteristics under a specific evaluation tensor.
In a second aspect, an embodiment of the present application provides an optical splitter port detection apparatus based on a multivariate algorithm, including:
the acquisition module is used for acquiring service information of at least one optical splitter, wherein the service information comprises attribute information and port information shot by the at least one optical splitter within a preset duration;
the first analysis module is used for respectively analyzing the attribute information and the port information based on at least one first preset analysis rule and at least one second preset analysis rule to respectively obtain a first resource occupation characteristic and a second resource occupation characteristic of each port of the at least one optical splitter;
the second analysis module is used for analyzing the first resource occupation characteristic and the second resource occupation characteristic by utilizing a predetermined multi-element algorithm to obtain a judgment result of whether the distribution of each port of at least one optical splitter is accurate.
In one embodiment, the attribute information includes: type of beam splitter and identification information; port information, comprising: the port identification information, the port connection tail fiber information, the port occupation state and the port output optical signals.
In one embodiment, the first preset analysis rule includes:
and obtaining the first resource occupation characteristic of each port of at least one optical splitter according to the type of the optical splitter and/or the identification information of the optical splitter, the identification information of the port, the occupation state of the port and the optical signal output by the port.
In one embodiment, the second preset analysis rule includes:
determining an optical resource allocation task corresponding to the optical splitter according to the type of the optical splitter and/or the identification information of the optical splitter;
and determining the second resource occupation characteristic of each port of at least one optical splitter according to the optical resource allocation task, the tail fiber information of the port connection and the optical signals output by the ports.
In one embodiment, the first resource occupancy feature comprises: the number of occupied ports of at least one optical splitter, the wavelength transmitted by each port and the specification attribute of the optical signal transmitted by each port; a second resource occupancy characteristic, comprising: the accuracy of the tail fiber information connected with each port of at least one optical splitter and the accuracy of the transmitted optical signals.
In one embodiment, the predetermined polynomial algorithm includes at least one polynomial algorithm selected from the following formulas (1) to (3):
Y=A×X，（1）
Y=X T ×A×X，（2）
Y=X T ×(X T ×A×X)，（3）
wherein Y is a target variable of a polynomial and is used for identifying the distribution accuracy of each port of at least one optical splitter, and X is a set of resource occupation characteristics of each port of at least one optical splitter, including a first resource occupation characteristic and a second resource occupation characteristic; a is an evaluation tensor of a preset dimension.
In one embodiment, the at least one polynomial algorithm includes at least one decision tree function; the at least one decision tree function comprises at least one decision branch for deciding a target variable using the set of resource occupancy characteristics under a specific evaluation tensor.
In a third aspect, an embodiment of the present application provides an apparatus, where the apparatus includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the method for detecting a port of a splitter based on a multivariate algorithm as described in the first aspect above is implemented.
In a fourth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program, where the computer program when executed by a processor implements a method for detecting a port of a splitter based on a multivariate algorithm as described in the first aspect above.
According to the multi-algorithm-based port detection algorithm for the optical splitters, service information of at least one optical splitter is obtained, wherein the service information comprises attribute information and port information shot by the at least one optical splitter within a preset duration; analyzing the attribute information and the port information based on at least one first preset analysis rule and at least one second preset analysis rule respectively to obtain a first resource occupation characteristic and a second resource occupation characteristic of each port of at least one optical splitter; and analyzing the first resource occupation characteristic and the second resource occupation characteristic by utilizing a predetermined multivariate algorithm to obtain a judgment result of whether the allocation of each port of at least one optical splitter is accurate. According to the scheme, the first resource occupation characteristic and the second resource occupation characteristic of the optical splitter are obtained based on the service information of the optical splitter without depending on manual experience, and further the first resource occupation characteristic and the second resource occupation characteristic are analyzed based on a multivariate algorithm, so that the efficiency and the quality of service processing are improved, and the experience effect of a user is improved while the increasing service demands are met.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required for the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a method for detecting ports of a splitter based on a multivariate algorithm according to a first embodiment of the present application;
fig. 2 is a schematic diagram of a splitter port detection device based on a multivariate algorithm according to a second embodiment of the present application;
fig. 3 is a schematic diagram of a splitter port detection device based on a multivariate algorithm according to a third embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
As used in this specification and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".
In addition, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
Referring to fig. 1, fig. 1 is a schematic flow chart of a method for detecting ports of a splitter based on a multivariate algorithm according to a first embodiment of the present application. In this embodiment, an execution body of the method for detecting a port of a splitter based on a multivariate algorithm is a device with a data processing function, and the device may be a personal computer, a server, or the like. The method for detecting the ports of the optical splitter based on the multivariate algorithm as shown in fig. 1 can comprise the following steps:
s101: and acquiring service information of at least one optical splitter, wherein the service information comprises attribute information and port information shot by the at least one optical splitter within a preset duration.
Wherein the attribute information includes: the type of the beam splitter and the identification information of the beam splitter; the port information includes: the port identification information, the port connection tail fiber information, the port occupation state and the port output optical signals.
Specifically, the types of the optical splitters include specifications of optical splitters, such as a single-mode optical splitter or a multimode optical splitter, a wavelength division multiplexing optical splitter or a dense wavelength division multiplexing optical splitter, and the like; the identification information of the optical splitter is a unique identifier for identifying and distinguishing the optical splitter. The identification information of the port is an identifier for marking and identifying the port; the pigtail information of the port connection is information for marking and describing the optical fiber connected to each port. It should be understood that the tail fibers correspondingly connected to the ports of the optical splitters of different types may be different or the same, and specifically may be preset according to the application scenario.
The occupation state of the ports comprises whether each port is occupied or not; the optical signal output by the port includes the wavelength, intensity, etc. of the output light.
The preset duration is a preset detection duration. The equipment can accurately judge the possible wrong port connection phenomenon of the optical splitter by acquiring the attribute information and the port information shot by at least one optical splitter within the preset time, because if the port connection of the optical splitter is wrong, the optical signal cannot be correctly transmitted, the problem of optical signal loss or optical signal intensity loss occurs, and periodic optical signal fluctuation or intermittent optical signal can occur due to the wrong port connection for a long time. Therefore, the attribute information and the port information shot by at least one optical splitter in the preset time period are acquired, and further the attribute information and the port information are analyzed, so that whether the port connection of the at least one optical splitter is wrong or not can be effectively judged.
According to the method and the device, whether the output optical signals have fluctuation or not or whether the intermittent optical signals exist or not can be judged by analyzing whether the acquired ports are in the preset time length, and whether the corresponding ports have the phenomenon of connection errors or not can be judged.
S102: and analyzing the attribute information and the port information based on at least one first preset analysis rule and at least one second preset analysis rule respectively to obtain a first resource occupation characteristic and a second resource occupation characteristic of each port of the at least one optical splitter.
Specifically, the device analyzes attribute information and port information of at least one optical splitter through at least one first preset analysis rule to obtain first resource occupation characteristics of each port of the at least one optical splitter; further, the device analyzes the attribute information and the port information of the at least one optical splitter according to at least one second preset analysis rule to obtain second resource occupation characteristics of each port of the at least one optical splitter.
Wherein, the first preset analysis rule includes: and obtaining the first resource occupation characteristic of each port of at least one optical splitter according to the type of the optical splitter and/or the identification information of the optical splitter, the identification information of each port, the occupation state of each port and the optical signals output by each port. Specifically, for each optical splitter, the type of the optical splitter and/or the identification information of the optical splitter are combined with the identification information of each port of the optical splitter, the occupation state of each port and the optical signals output by each port, the number of occupied ports of the optical splitter is calculated, and the wavelength and specification attribute of the optical signals output by each occupied port are determined, so that the first resource occupation characteristic is obtained.
Specifically, the corresponding optical splitter can be identified according to the type of the optical splitter or the identification information of the optical splitter, and the wavelength and specification attribute of the optical signal output by each port of the optical splitter can be determined according to the identified identification information of each port of the optical splitter, the occupancy state of each port and the optical signal output by each port. Wherein the specification attribute comprises single mode or multi-mode.
Specifically, the first resource occupancy characteristic includes: the number of occupied ports of at least one optical splitter, the wavelength transmitted by each port, and the specification attribute of the optical signal transmitted by each port.
A second preset analysis rule comprising: determining an optical resource allocation task corresponding to the optical splitter according to the type of the optical splitter and/or the identification information of the optical splitter; and determining the second resource occupation characteristic of each port of at least one optical splitter according to the optical resource allocation task, the tail fiber information connected with each port and the optical signals output by each port.
The optical resource allocation task corresponding to each optical splitter may be determined in advance according to the actual application. Specifically, the optical resource allocation task corresponding to each optical splitter includes: and transmitting the specific optical signal to the tail fiber connected with the corresponding port through the specific port.
Specifically, according to the type of the optical splitter and/or the identification information of the optical splitter, the optical resource allocation task of the corresponding optical splitter can be determined; after the optical resource allocation task of the corresponding optical splitter is obtained, the mapping relation among the ports, the optical signals and the tail fiber information of each optical splitter, which are established in advance, can be traversed according to the optical resource allocation task and the identification information of each port, and the target optical signals which are required to be transmitted by each port and the target tail fiber information which is required to be connected are determined; and comparing the target optical signal and the target tail fiber information with the tail fiber information actually connected with each port and the optical signal actually output by each port respectively to obtain the accuracy of the tail fiber information connected with each port and the accuracy of the output optical signal.
Specifically, the second resource occupancy characteristic includes: the accuracy of the tail fiber information connected with each port of at least one optical splitter and the accuracy of the transmitted optical signals.
S103: and analyzing the first resource occupation characteristic and the second resource occupation characteristic by utilizing a predetermined multivariate algorithm to obtain a judgment result of whether the allocation of each port of at least one optical splitter is accurate.
Wherein the predetermined polynomial algorithm includes at least one polynomial algorithm selected from the following formulas (1) to (3):
Y=A×X，（1）
Y=X T ×A×X，（2）
Y=X T ×(X T ×A×X)，（3）
wherein Y is a target variable of a polynomial and is used for identifying the distribution accuracy of each port of at least one optical splitter, and X is a set of resource occupation characteristics of each port of at least one optical splitter, including a first resource occupation characteristic and a second resource occupation characteristic; a is an evaluation tensor of a preset dimension.
In one embodiment, the at least one polynomial algorithm includes at least one decision tree function; the at least one decision tree function comprises at least one decision branch for deciding a target variable using the set of resource occupancy characteristics under a specific evaluation tensor.
In specific implementation, the evaluation tensor a may be a one-dimensional evaluation tensor, a two-dimensional evaluation tensor, or a three-dimensional evaluation tensor, which is of a preset dimension. Preferably, a may be a symmetric tensor. For example, a may be a 3 x 3 tensor. The set X of resource occupancy characteristics for each port of at least one of the splitters may be represented by a vector or matrix. Specifically, the first resource occupation characteristic and the second resource occupation characteristic of each port of at least one optical splitter are respectively normalized to obtain a corresponding vector or matrix.
Correspondingly, the target variable Y identifying the allocation accuracy of each port of at least one of the splitters may also be represented by a vector or matrix.
For example, the at least one polynomial algorithm comprises at least one decision tree function in the following equations (4) to (6):
，（4）
，（5）
，（6）
where f is a conditional expression, A is a specific evaluation tensor,、/>and +.>For predetermined coefficients, i, j and k are each independent integers from 1 to N, for identifying each port of at least one optical splitter; />、/>And +.>Respectively corresponding to the ith, jth and kth vectors in the set representing the resource occupancy characteristicsOr a matrix, F is a value corresponding to the target variable Y determined under a specific evaluation tensor.
It should be noted that in other embodiments, the multivariate evaluation algorithm may comprise a decision tree of more complex structure, such as a second order decision tree. Specifically, the decision tree is selected to determine the desired target variable depending on the characteristic values in the set of resource occupancy characteristics, depending on whether or not it is possible to satisfy the set of characteristic values under a specific evaluation tensor. Wherein the evaluation tensor is adapted such that the characteristic values in the characteristic set are linearly independent, whereby a corresponding unique target variable can be derived based on the different characteristic values.
It should be noted that, the value of the target variable Y is usually represented by 0 and 1, where 0 is used to represent that the corresponding port allocation is wrong, and 1 is used to represent that the corresponding port allocation is accurate.
In the embodiment of the application, the service information of at least one optical splitter is obtained, wherein the service information comprises attribute information and port information shot by the at least one optical splitter within a preset duration; analyzing the attribute information and the port information based on at least one first preset analysis rule and at least one second preset analysis rule respectively to obtain a first resource occupation characteristic and a second resource occupation characteristic of each port of at least one optical splitter; and analyzing the first resource occupation characteristic and the second resource occupation characteristic by utilizing a predetermined multivariate algorithm to obtain a judgment result of whether the allocation of each port of at least one optical splitter is accurate. According to the scheme, the first resource occupation characteristic and the second resource occupation characteristic of the optical splitter are obtained based on the service information of the optical splitter without depending on manual experience, and further the first resource occupation characteristic and the second resource occupation characteristic are analyzed based on a multivariate algorithm, so that the efficiency and the quality of service processing are improved, and the experience effect of a user is improved while the increasing service demands are met.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not limit the implementation process of the embodiment of the present application in any way.
Referring to fig. 2, fig. 2 is a schematic diagram of a splitter port detection device based on a multivariate algorithm according to a third embodiment of the present application. The included modules are integrated in a multi-algorithm-based splitter port detection device in a hardware or software manner and are used for executing the steps in the corresponding embodiment of fig. 1. Refer specifically to the description of the corresponding embodiment in fig. 1. For convenience of explanation, only the portions related to the present embodiment are shown. Referring to fig. 2, the optical splitter port detection apparatus 20 based on the multivariate algorithm includes:
an obtaining module 201, configured to obtain service information of at least one optical splitter, where the service information includes attribute information and port information that are shot by the at least one optical splitter within a preset duration;
a first analysis module 202, configured to analyze the attribute information and the port information based on at least one first preset analysis rule and at least one second preset analysis rule, to obtain a first resource occupancy characteristic and a second resource occupancy characteristic of each port of the at least one optical splitter, respectively;
and the second analysis module 203 is configured to analyze the first resource occupancy characteristic and the second resource occupancy characteristic by using a predetermined multivariate algorithm, so as to obtain a determination result of whether the allocation of each port of the at least one optical splitter is accurate.
In one embodiment, the attribute information includes: the type of the beam splitter and the identification information of the beam splitter; the port information includes: the port identification information, the port connection tail fiber information, the port occupation state and the port output optical signals.
In one embodiment, the first preset analysis rule includes:
and obtaining the first resource occupation characteristic of each port of at least one optical splitter according to the type of the optical splitter and/or the identification information of the optical splitter, the identification information of each port, the occupation state of each port and the optical signals output by each port.
In one embodiment, the second preset analysis rule includes:
determining an optical resource allocation task corresponding to the optical splitter according to the type of the optical splitter and/or the identification information of the optical splitter;
and determining the second resource occupation characteristic of each port of at least one optical splitter according to the optical resource allocation task, the tail fiber information connected with each port and the optical signals output by each port.
In one embodiment, the first resource occupancy feature comprises: the number of occupied ports of at least one optical splitter, the wavelength transmitted by each port and the specification attribute of the optical signal transmitted by each port; a second resource occupancy characteristic, comprising: the accuracy of the tail fiber information connected with each port of at least one optical splitter and the accuracy of the transmitted optical signals.
In one embodiment, the predetermined polynomial algorithm includes at least one polynomial algorithm selected from the following formulas (1) to (3):
Y=A×X，（1）
Y=X T ×A×X，（2）
Y=X T ×(X T ×A×X)，（3）
wherein Y is a target variable of a polynomial and is used for identifying the distribution accuracy of each port of at least one optical splitter, and X is a set of resource occupation characteristics of each port of at least one optical splitter, including a first resource occupation characteristic and a second resource occupation characteristic; a is an evaluation tensor of a preset dimension.
In one embodiment, the at least one polynomial algorithm includes at least one decision tree function; the at least one decision tree function comprises at least one decision branch for deciding a target variable using the set of resource occupancy characteristics under a specific evaluation tensor.
Referring to fig. 3, fig. 3 is a schematic diagram of a splitter port detection apparatus based on a multivariate algorithm according to a fourth embodiment of the present application. As shown in fig. 3, the optical splitter port detection apparatus 3 based on the multivariate algorithm includes: a processor 30, a memory 31, and a computer program 32 stored in the memory 31 and executable on the processor 30, such as a splitter port detection program based on a multivariate algorithm. The steps of the above-described respective embodiments of the multivariate algorithm-based splitter port detection method are implemented when the processor 30 executes the computer program 32, such as steps S101 to S103 shown in fig. 1. Alternatively, the processor 30 may implement the functions of the modules/units in the above-described apparatus embodiments when executing the computer program 32, for example, the functions of the acquisition module 201 to the second analysis module 203 shown in fig. 2.
By way of example, the computer program 32 may be partitioned into one or more modules/units, which are stored in the memory 31 and executed by the processor 30 to complete the present application. One or more of the modules/units may be a series of computer program instruction segments capable of performing a specific function for describing the execution of the computer program 32 in the multivariate algorithm based splitter port detection device 3. For example, the computer program 32 may be divided into an acquisition module, a first analysis module and a second analysis unit, each module functioning specifically as follows:
the acquisition module is used for acquiring service information of at least one optical splitter, wherein the service information comprises attribute information and port information shot by the at least one optical splitter within a preset duration;
the first analysis module is used for respectively analyzing the attribute information and the port information based on at least one first preset analysis rule and at least one second preset analysis rule to respectively obtain a first resource occupation characteristic and a second resource occupation characteristic of each port of the at least one optical splitter;
and the second analysis module is used for analyzing the first resource occupation characteristic and the second resource occupation characteristic by utilizing a predetermined multi-element algorithm to obtain a judgment result of whether the allocation of each port of at least one optical splitter is accurate.
The optical splitter port detection apparatus 3 based on the multivariate algorithm may include, but is not limited to, a processor 30, a memory 31. It will be appreciated by those skilled in the art that fig. 3 is merely an example of a multi-element algorithm-based splitter port detection device 3 and is not meant to be limiting of the multi-element algorithm-based splitter port detection device 3, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the multi-element algorithm-based splitter port detection device may also include input-output devices, network access devices, buses, etc.
The processor 30 may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 31 may be an internal storage unit of the optical splitter port detection apparatus 3 based on a multivariate algorithm, for example, a hard disk or a memory of the optical splitter port detection apparatus 3 based on a multivariate algorithm. The memory 31 may be an external storage device of the optical splitter port detection apparatus 3 based on a multivariate algorithm, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like provided on the optical splitter port detection apparatus 3 based on a multivariate algorithm. Further, the optical splitter port detection apparatus 3 based on the multivariate algorithm may further include both an internal storage unit and an external storage apparatus of the optical splitter port detection apparatus 3 based on the multivariate algorithm. The memory 31 is used to store a computer program and other programs and data required for the optical splitter port detection apparatus based on the multivariate algorithm. The memory 31 may also be used to temporarily store data that has been output or is to be output.
It should be noted that, because the content of information interaction and execution process between the above devices/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein again.
The embodiment of the application also provides a network device, which comprises: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, the processor implementing the steps in any of the various method embodiments described above when the computer program is executed.
The embodiments of the present application also provide a computer readable storage medium storing a computer program, where the computer program when executed by a processor implements steps of the foregoing method embodiments.
Embodiments of the present application provide a computer program product which, when run on a mobile terminal, causes the mobile terminal to perform steps that may be performed in the various method embodiments described above.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application implements all or part of the flow of the method of the above embodiments, and may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, where the computer program, when executed by a processor, may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing device/terminal apparatus, recording medium, computer Memory, read-Only Memory (ROM), random access Memory (RAM, random Access Memory), electrical carrier signals, telecommunications signals, and software distribution media. Such as a U-disk, removable hard disk, magnetic or optical disk, etc. In some jurisdictions, computer readable media may not be electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other manners. For example, the apparatus/network device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (9)
1. The method for detecting the ports of the optical splitter based on the multivariate algorithm is characterized by comprising the following steps of:
acquiring service information of at least one optical splitter, wherein the service information comprises attribute information and port information shot by the at least one optical splitter within a preset duration;
analyzing the attribute information and the port information based on at least one first preset analysis rule and at least one second preset analysis rule respectively to obtain a first resource occupation characteristic and a second resource occupation characteristic of each port of the at least one optical splitter;
analyzing the first resource occupation characteristic and the second resource occupation characteristic by utilizing a predetermined multivariate algorithm, and judging whether each port of the at least one optical splitter is accurately allocated; the predetermined multivariate algorithm includes at least one polynomial algorithm selected from the following formulas (1) to (3):
Y＝A×X， (1)
Y＝X T ×A×X， (2)
Y＝X T ×(X T ×A×X)， (3)
wherein Y is a target variable of a polynomial, and is used for identifying the distribution accuracy of each port of the at least one optical splitter, and X is a set of resource occupation characteristics of each port of the at least one optical splitter, including a first resource occupation characteristic and a second resource occupation characteristic; a is an evaluation tensor of a preset dimension.
2. The method for detecting a port of a splitter based on a multivariate algorithm according to claim 1, wherein the attribute information comprises: type of beam splitter and identification information; the port information includes: the port identification information, the port connection tail fiber information, the port occupation state and the port output optical signals.
3. The method for detecting ports of a splitter based on a multivariate algorithm according to claim 2, wherein the first preset analysis rule comprises:
and obtaining the first resource occupation characteristic of each port of the at least one optical splitter according to the type of the optical splitter and/or the identification information of the optical splitter, the identification information of the port, the occupation state of the port and the optical signal output by the port.
4. The method for detecting ports of a splitter based on a multivariate algorithm according to claim 2, wherein the second preset analysis rule comprises:
determining an optical resource allocation task corresponding to the optical splitter according to the type of the optical splitter and/or the identification information of the optical splitter;
and determining second resource occupation characteristics of each port of the at least one optical splitter according to the optical resource allocation task, the tail fiber information connected with the port and the optical signals output by the port.
5. The method for detecting ports of a splitter based on a multivariate algorithm according to claim 1, wherein the first resource occupancy characteristic comprises: the number of occupied ports of the at least one optical splitter, the wavelength transmitted by each port and the specification attribute of the optical signal transmitted by each port; the second resource occupancy characteristic includes: and the accuracy of the tail fiber information connected with each port of the at least one optical splitter and the accuracy of the transmission optical signals.
6. The method of multivariate algorithm based splitter port detection of claim 1, wherein the at least one polynomial algorithm comprises at least one decision tree function; the at least one decision tree function comprises at least one decision branch for deciding the target variable using the set of resource occupancy characteristics under a specific evaluation tensor.
7. A splitter port detection device based on a multivariate algorithm, comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring service information of at least one optical splitter, and the service information comprises attribute information and port information shot by the at least one optical splitter in a preset duration;
the first analysis module is used for respectively analyzing the attribute information and the port information based on at least one first preset analysis rule and at least one second preset analysis rule to respectively obtain a first resource occupation characteristic and a second resource occupation characteristic of each port of the at least one optical splitter;
the second analysis module is used for analyzing the first resource occupation characteristic and the second resource occupation characteristic by utilizing a predetermined multivariate algorithm to obtain a judgment result of whether the allocation of each port of the at least one optical splitter is accurate or not; the predetermined multivariate algorithm includes at least one polynomial algorithm selected from the following formulas (1) to (3):
Y＝A×X， (1)
Y＝X T ×A×X， (2)
Y＝X T ×(X T ×A×X)， (3)
wherein Y is a target variable of a polynomial, and is used for identifying the distribution accuracy of each port of the at least one optical splitter, and X is a set of resource occupation characteristics of each port of the at least one optical splitter, including a first resource occupation characteristic and a second resource occupation characteristic; a is an evaluation tensor of a preset dimension.
8. An apparatus, the apparatus comprising: a processor, a memory and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 6.
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