Fault decision method, system, medium and electronic equipment based on immune algorithm

Abstract

The present invention relates to a fault decision method, system, medium and electronic equipment based on immune algorithm, and relates to the technical field of base station related data processing, including: establishing a database, including multiple historical fault information of multiple base stations, each historical fault information includes multiple first keywords corresponding to the fault and the corresponding cause; assigning different weights X to each cause in accordance with the standard; assigning different weights Y from large to small to multiple base stations in accordance with the value from high to low; when a base station fails, determining the cause according to the distribution of the first keywords involved in different historical fault information; calculating the fault severity index of the base station according to the weight X and the weight Y; and deciding the resource allocation of the corresponding fault base station according to the fault severity index. The present invention solves the problem in the prior art that when multiple base stations fail, there is a lack of reasonable resource allocation decision, which easily leads to loss expansion.

Description

Technical Field

[0001] The present invention relates to the technical field of base station related data processing, and in particular to a fault decision method, system, medium and electronic equipment based on immune algorithm. Background Art

[0002] With the rapid development of my country's mobile communications, the communications industry has faced many challenges. It must not only continuously improve communication efficiency, but also better ensure communication quality. It must improve communication networks from multiple perspectives to reduce inherent losses and deficiencies.

[0003] Base stations are very important nodes in communication systems. Once it is detected that the signal within the coverage area of ​​the base station antenna is interrupted or seriously weakened, it is possible that the base station has been decommissioned, which will seriously affect the normal calls of users within the coverage area.

[0004] When multiple base stations in a region are out of service due to faults, staff often allocate resources for repair and maintenance in chronological order; however, there are many reasons for base station outages, such as heavy rain, examinations, power outages, earthquakes, etc. The duration of base station outages or the difficulty of repairs caused by different reasons vary greatly. In addition, if the staff is not clear about the reasons for the base station outages, it is easy to cause a lack of reasonable resource allocation among the above-mentioned faulty base stations, resulting in the possibility that base stations with small impact and small losses are handled first, while base stations with large impact and large losses are delayed, which increases the losses. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a fault decision method, system, medium and electronic equipment based on an immune algorithm, which solves the problem in the prior art that when multiple base stations fail, there is a lack of reasonable resource allocation decisions, which easily leads to increased losses.

[0006] At least one embodiment of the present invention provides a fault decision method based on an immune algorithm, comprising the following steps:

[0007] Establishing a database, the database including a plurality of base station data, each of the base station data including a plurality of historical fault information, each of the historical fault information including a plurality of first keywords corresponding to the fault and a cause of the fault;

[0008] Assigning different weights X to each of the causes in accordance with the standards, wherein the standards include the difficulty of troubleshooting and the attribution of the fault factors;

[0009] Assign different weights Y from large to small to multiple base stations according to their values ​​from high to low;

[0010] When a base station fails, a new complaint ticket is obtained, wherein the new complaint ticket contains multiple second keywords;

[0011] For each of the second keywords, determine the generation cause corresponding to the new complaint work order according to the distribution of the first keyword identical to the second keyword in different historical fault information;

[0012] Calculate the fault severity index of the base station according to the weight X corresponding to the cause and the weight Y corresponding to the base station where the fault occurs;

[0013] According to the fault severity index, a decision is made on resource allocation of the corresponding faulty base station.

[0014] At least one embodiment of the present invention further provides a fault decision system based on an immune algorithm, comprising:

[0015] A data storage module, wherein the data storage module has a database, wherein the database includes a plurality of base station data, each of the base station data includes a plurality of historical fault information, and each of the historical fault information includes a plurality of first keywords corresponding to the fault and a corresponding cause of occurrence;

[0016] The weight assignment module a assigns different weights X to each of the causes in the data storage module in accordance with the standard, wherein the standard includes the difficulty of troubleshooting and the attribution of the fault factors;

[0017] The weight assignment module b assigns different weights Y from large to small to multiple base stations in the database according to their values ​​from high to low;

[0018] A fault cause judgment module, when a base station fails, obtains a new complaint work order, wherein the new complaint work order contains multiple second keywords; for each of the second keywords, the cause of the new complaint work order is determined according to the distribution of the first keyword that is the same as the second keyword in different historical fault information;

[0019] A fault severity index calculation module calculates the fault severity index of the base station according to the weight X corresponding to the cause and the weight Y corresponding to the base station where the fault occurs;

[0020] The decision module decides resource allocation of the corresponding faulty base station according to the fault severity index.

[0021] At least one embodiment of the present invention further provides a computer-readable medium, wherein instructions are stored in the computer-readable storage medium. When the instructions are executed on a terminal device, the terminal device executes the steps of the fault decision method based on the immune algorithm as described in any one of claims 1 to 7.

[0022] At least one embodiment of the present invention also provides an electronic device, comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that when the processor executes the program, the steps of the fault decision method based on the immune algorithm as described in any one of claims 1 to 7 are implemented.

[0023] The technical solution disclosed in the present invention has at least the following beneficial effects:

[0024] By establishing a database, the second keyword of the new complaint ticket during the decommissioning period of the base station can be used to search for the first keyword corresponding to the above complaint ticket in the database, and accurately determine the fault cause of the decommissioned base station;

[0025] The fault severity index corresponding to the base station is calculated by using the weight Y assigned to the cause of the fault and the weight X assigned to the base station where the fault occurs.

[0026] At this point, the staff can use the above fault severity index as a basis for more reasonable and scientific decision-making on resource allocation, thereby avoiding the situation where base stations with small impact and small losses are processed first, and base stations with large impact and large losses are processed later, thereby reducing the losses caused by base station decommissioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of one embodiment of a fault decision method based on immune algorithm according to the present invention;

[0028] Figure 2 It is a flow chart of one embodiment of the fault decision system based on immune algorithm of the present invention;

[0029] Figure 3 The figure is a flow chart of another embodiment of the fault decision method based on immune algorithm of the present invention. DETAILED DESCRIPTION

[0030] The principles and features of the present invention are described below. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0031] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0032] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0033] The present invention provides a fault decision method based on immune algorithm, please refer to Figure 1 As shown, including:

[0034] S1. Establish a database, wherein the database includes a plurality of base station data, each of the base station data includes a plurality of historical fault information, and each of the historical fault information includes a plurality of first keywords corresponding to the fault and a cause of the fault;

[0035] Specifically, all base station data in a certain area (the whole province is used as the area in this embodiment) are obtained from the big data lake, and the above base station data are sorted so that each historical fault information corresponds to a base station data, wherein the base station data refers to various information about a base station, including the name of the corresponding base station, base station number, base station value, city, district, county, cause of historical faults, and fault duration;

[0036] Extract historical fault complaint work orders and historical fault handling solutions corresponding to each fault in the big data lake, obtain multiple first keywords in the historical fault complaint work orders and historical fault handling solutions, and store the multiple first keywords corresponding to each fault together in the corresponding historical fault information.

[0037] S2. Assign different weights X to each cause in accordance with the standards, where the standards include the difficulty of troubleshooting and the attribution of the fault factors;

[0038] Accordingly, the weight X corresponding to each fault cause is stored together with the information of the corresponding fault cause;

[0039] S3, assigning different weights Y from large to small to multiple base stations according to their values ​​from high to low;

[0040] Correspondingly, the weight X corresponding to each base station is stored together in the fault information including the above base stations;

[0041] S4. When a base station fails, a new complaint ticket is obtained, and the new complaint ticket contains multiple second keywords;

[0042] For each second keyword, determine the cause according to the distribution of the first keyword identical to the second keyword in different historical fault information;

[0043] S5. Calculate the fault severity index of the base station according to the weight X corresponding to the cause and the weight Y corresponding to the base station where the fault occurs;

[0044] S6. According to the fault severity index, decide on resource allocation for the faulty base station.

[0045] After adopting the above solution:

[0046] By establishing a database, the second keyword of the new complaint ticket during the decommissioning period of the base station can be used to search for the first keyword corresponding to the above complaint ticket in the database, and accurately determine the fault cause of the decommissioned base station;

[0047] The fault severity index corresponding to the base station is calculated by using the weight Y assigned to the cause of the fault and the weight X assigned to the base station where the fault occurs.

[0048] At this point, the staff can use the above fault severity index as a basis for more reasonable and scientific decision-making on resource allocation, thereby avoiding the situation where base stations with small impact and small losses are processed first, and base stations with large impact and large losses are processed later, thereby reducing the losses caused by base station decommissioning.

[0049] Further, for each of the second keywords, determining the cause according to the distribution of the first keyword identical to the second keyword in different historical fault information specifically includes:

[0050] In each historical fault information, a correlation value Z is assigned to each first keyword according to the correlation between each first keyword and the cause;

[0051] The sum of the association values ​​Z of the first keywords that are the same as the second keywords in each piece of historical fault information is counted respectively;

[0052] The historical fault information corresponding to the largest sum of the correlation values ​​Z is determined, and the cause of the fault in the historical fault information is obtained.

[0053] For example, in the event that a historical failure causes a base station to be out of service;

[0054] When one of the faults is caused by heavy rain, the first keyword "heavy rain" corresponds to a correlation value Z of 1, the keyword "power outage" corresponds to a correlation value Z of 0.5, and the keyword "fire" corresponds to a correlation value Z of 0;

[0055] When another historical fault cause is fire, the associated value Z of the keyword "heavy rain" is 0, the associated value Z of the keyword "power outage" is 0.5, and the associated value Z of the keyword "fire" is 1;

[0056] At this time, if a base station is out of service, the sum of the association values ​​Z of the first keywords that are the same as the second keyword in each historical fault information can be counted based on the second keyword in the new complaint ticket of the citizen, such as "heavy rain", "power outage", etc., such as:

[0057] When the cause of the calculation failure is heavy rain, the sum of the above correlation values ​​Z is 1+0.5=1.5;

[0058] When the cause of the calculated fault is fire, the sum of the above-mentioned correlation values ​​Z is 0+0.5=0.5;

[0059] Obviously, according to the comparison of the sum of the correlation values ​​of the above different fault causes, referring to the above results, the sum of the correlation values ​​of the fault cause being heavy rain is greater than the sum of the correlation values ​​of the fault cause being fire. It can be judged that the cause of this fault is heavy rain.

[0060] Furthermore, if the fault factors are internal or external, each cause is assigned a different weight X in accordance with the standard, including:

[0061] When the fault factor is attributed to an internal factor, the value of weight X is 1;

[0062] When the fault factor is classified as an external factor, each fault cause is classified into the first, second, third and fourth categories of factors according to the difficulty of solving the fault from easy to difficult; the weight X assigned to all fault causes in the first category of factors is 0, the weight X assigned to all fault causes in the second category of factors is 0.2, the weight X assigned to all fault causes in the third category of factors is 0.4, and the weight X assigned to all fault causes in the fourth category of factors is 0.7.

[0063] Specifically, the above internal factors include the base station staff's manual shutdown of the base station;

[0064] The above-mentioned factors are completely uncontrollable external factors, such as signal shielding caused by the college entrance examination, the high school entrance examination or other major events. Such problems do not need to be solved and can be recovered in a short time, so the weight X assigned is 0;

[0065] The above two types of factors are external factors of a smaller degree that are beyond human control, such as increased base station load caused by residents' activities, heavy rain, heavy snow, small-scale power outages, etc.;

[0066] The above three types of factors are external factors that are largely beyond the control of some forces, such as large-scale power failures, major traffic accidents, etc.

[0067] The above four categories of factors are serious external factors that are beyond human control, such as earthquakes, fires, floods, typhoons and other natural disasters.

[0068] Furthermore, multiple base stations are assigned different weights Y from large to small in order of value from high to low, specifically including:

[0069] Multiple base stations in the same area are classified into Class A base stations, Class B base stations, Class C base stations and Class D base stations in order of value from high to low, among which the weight Y assigned to all base stations in Class A base stations is 0.8, the weight Y assigned to all base stations in Class B base stations is 0.6, the weight Y assigned to all base stations in Class C base stations is 0.4, and the weight Y assigned to all base stations in Class D base stations is 0.2.

[0070] Different base stations are assigned weights Y of varying sizes to reflect the relative importance of the base stations.

[0071] Specifically, according to the weight X corresponding to the cause of the fault, combined with the weight Y corresponding to the base station where the fault occurs, the fault severity index of the base station is calculated, and the calculation formula is:

[0072] Z=X*Y

[0073] Wherein, Z represents the fault severity index of the base station.

[0074] By combining the value weight Y of the base station and the fault handling difficulty weight X, the fault severity index Z of the corresponding faulty base station can be calculated. When multiple faults occur in the same area, they can be sorted by the size of the above fault severity index and related resources such as maintenance personnel can be allocated reasonably and scientifically.

[0075] The present invention also provides another embodiment, which is different from the above embodiment in that it also includes determining the immunity index of the base station when encountering a fault according to the weight X, the weight Y and the factor attribution, and the immunity index represents the immunity capability of different base stations when dealing with different faults;

[0076] The immune de-service duration of the base station is determined based on the immune index and the base station de-service duration. The immune de-service duration represents the degree of impact of different base stations on surrounding areas under different faults.

[0077] Specifically, when the factor is attributed to internal factors, the immunity index is 1;

[0078] When the factor is classified as an external factor and belongs to a category of factors, the immunity index is 0;

[0079] When the factor is classified as an external factor and belongs to the second, third or fourth category, the calculation equation of the immunity index is:

[0080] U=Y(1-X)

[0081] Among them, U is the immune index;

[0082] According to the immunity index and the base station decommissioning time, the base station immunity decommissioning time is determined, and the calculation formula is:

[0083] T=t*U

[0084] Among them, T represents the base station immune decommissioning time, and t represents the base station decommissioning time.

[0085] For example, take the failure analysis of a base station out of service at a certain time period in a certain university in Wuhan as an example:

[0086] There are 21 base stations in a university in Wuhan. Three base stations were out of service during the above period:

[0087] Base station 1: Class A base station, the cause of the fault is power failure (second-class factor), and the outage duration is 35 minutes. The fault severity index of base station 1 is: 0.8*0.2=0.16, the immunity index of base station 1 is: 0.8*0.8=0.64, and the immunity outage duration of base station 1 is: 0.64*35=22.4 (minutes);

[0088] Base station 2: Class C base station, the cause of the fault is the civil service examination (a type of factor), and the outage duration is 180 minutes. The fault severity index of base station 2 is: 0.4*0=0, the immunity index of base station 2 is: 0.4*0=0, and the immunity outage duration of base station 2 is: 0*180=0 (minutes);

[0089] Base station 3: Class B base station. The cause of the fault is campus recruitment activities (second-class factor). The outage time is 22 minutes. The fault severity index of base station 3 is: 0.6*0.2=0.12, the immunity index of base station 3 is: 0.6*0.8=0.48, and the immunity outage time of base station 3 is 0.48*22=10.56 (minutes).

[0090] Based on the calculation results of the above fault severity index, we can derive the fault severity ranking of each base station that was out of service during the above time period: base station 1> base station 3> base station 2. At this time, the staff can assign more maintenance personnel to base station 1 and give priority to it based on the above fault severity ranking, assign relatively fewer maintenance personnel to base station 3, and no maintenance personnel is required to base station 2.

[0091] At the same time, the calculation of the above-mentioned immune decommissioning time can be used to represent the number of minutes of decommissioning time that should actually be included in the assessment of these three base stations when external factors are shielded and various force majeure influences are taken into account, so as to reflect the degree of impact of the base station decommissioning on the surrounding areas. This is more scientific and objective than the existing method of directly adding up the time without any processing.

[0092] Of course, the average immunization deservice time of each base station in the area during the above time period can also be calculated, that is, (10.56+22.4) / 21=0.52 (minutes), to obtain the average immunization deservice time of the area, so as to facilitate the subsequent planning or maintenance of the base stations in the area by the base station staff based on the above average immunization deservice time.

[0093] In this embodiment, by establishing a database, the second keyword of the new complaint ticket during the decommissioning of the base station can be used to search for the first keyword corresponding to the database in the complaint ticket, and accurately determine the fault cause of the decommissioned base station;

[0094] The fault severity index corresponding to the base station is calculated by using the weight Y assigned to the cause of the fault and the weight X assigned to the base station where the fault occurs.

[0095] Analyze the fault factors, calculate the immunity index of the base station when it encounters this fault, and the average outage time of the base station;

[0096] At this time, the staff can use the above fault severity index as a basis for more reasonable and scientific decision-making on resource allocation, thereby avoiding the situation where base stations with small impact and small losses are processed first, and base stations with large impact and large losses are processed later, thereby reducing the losses caused by the base station decommissioning; the actual impact of the base station decommissioning event on the area can be analyzed through the average decommissioning time of the base station

[0097] This embodiment also includes outputting the corresponding base station number, the cause of the fault, the fault severity index, the immunity index, the immunity decommissioning time and the average immunity decommissioning time of each base station in a certain area and within a certain time period from the report to facilitate subsequent observation and analysis by the staff.

[0098] The present invention also provides another embodiment, please refer to Figure 3 As shown, specifically:

[0099] Get the fault information list, including:

[0100] Pull and organize multiple base station data into the database; the specific contents are as follows: Pull base station data: obtain the service withdrawal records of all base stations in the province within the specified time period from the big data lake, including the time point and duration of each service withdrawal. At the same time, by querying the big data lake performance indicators, analyze the traffic data of the base station within the specified time period to determine whether it is in a zero traffic state; Organize base station data: organize historical fault information into a list in the specified format, including detailed information such as the base station name, base station number, base station value level, city, district, county, cause of the fault, and duration of the fault for each fault, and store it in the fault database;

[0101] Analyze the faulty base station level, including:

[0102] In order to facilitate calling and management, the base station value weight Y and the weight X assigned to the cause of the fault are stored in the same weight table, which contains the weight type and the corresponding weight value; the fault information is associated with the weight table to obtain the base station value weight Y and the weight X assigned to the cause of the fault corresponding to each fault information; according to the name of the base station with a new fault, the value weight Y of the base station is determined;

[0103] Failure cause analysis, including:

[0104] Use the base station name and historical fault information to find the corresponding record in the historical complaint ticket, extract the first keyword in the complaint handling plan to distinguish the cause of the fault; match the second keyword in the new complaint ticket with the first keyword to determine the cause of the current fault;

[0105] Calculate the fault severity index, including:

[0106] The fault severity index of the base station is calculated by multiplying the weight corresponding to the cause of the fault by the value weight of the base station where the fault occurs.

[0107] Calculate immune indices, including:

[0108] Determine the immunity index of the base station when encountering a fault based on the base station value weight Y, the weight X assigned to the cause of the fault, and the factor attribution;

[0109] Indicators calculated based on the index include:

[0110] For example, to calculate the duration indicators, take the immune decommissioning duration as an example, calculate the decommissioning duration after immunization according to the algorithm of "actual decommissioning duration * immune index" for multiple decommissioning records of a single base station, and then add up the duration of multiple decommissioning records to obtain the total decommissioning duration data of the base station before and after immunization in the specified time period. Then aggregate the duration of all base stations in the statistical area to obtain the total decommissioning duration and average decommissioning duration in the area (the average decommissioning duration is the total decommissioning duration divided by the total number of base stations). This data can represent the statistical value of the key indicator "decommissioning duration" under the traditional algorithm, as well as the statistical value of this indicator under the immune algorithm. Compared with the traditional algorithm, the immune algorithm shields external factors and force majeure factors, and is more scientific and reliable; to calculate the quantity indicators, take the number of zero-flow base stations as an example, first query the fault information table to determine whether each base station has zero flow in the specified time period. The number of zero-flow base stations is the number of zero-flow base stations before immunization, and adding up the immune indexes of zero-flow base stations is the number of zero-flow base stations after immunization. This data can represent the statistical value of the key indicator "number of zero-flow cells" under the traditional algorithm, as well as the statistical value of this indicator under the immune algorithm. Compared with the traditional algorithm, the immune algorithm shields external factors and force majeure factors, and is more scientific and reliable;

[0111] Output analysis report, including:

[0112] The sorted failure statistics before and after immunization are output according to the specified dimensions (such as districts, cities, districts and counties), thus completing the immunization analysis report output process.

[0113] The present invention also provides a fault decision system based on immune algorithm, please refer to Figure 2 As shown, including:

[0114] A data storage module, wherein the data storage module has a database, wherein the database includes a plurality of historical fault information of a plurality of base stations, and each piece of historical fault information includes a plurality of first keywords corresponding to the fault and a corresponding cause of the fault;

[0115] The weight assignment module a assigns different weights X to each cause in the data storage module according to the standard, wherein the standard includes the difficulty of troubleshooting and the attribution of the fault factors;

[0116] The weight assignment module b assigns different weights Y from large to small to multiple base stations in the database according to their values ​​from high to low;

[0117] The fault cause judgment module obtains a new complaint ticket when a base station fails. The new complaint ticket contains multiple second keywords. For each second keyword, the cause is determined based on the distribution of the first keyword that is the same as the second keyword in different historical fault information.

[0118] The fault severity index calculation module calculates the fault severity index of the base station according to the weight X corresponding to the cause and the weight Y corresponding to the base station where the fault occurs;

[0119] The decision module decides the resource allocation of the corresponding faulty base station according to the fault severity index.

[0120] Furthermore, when the fault cause determination module is analyzing the cause of the base station fault:

[0121] In each fault information, a different correlation value Z is assigned to each first keyword according to the correlation between each first keyword and the cause of the fault;

[0122] For each second keyword, sequentially calculate the association value Z of the first keyword that is the same as the second keyword in different historical fault information;

[0123] The cause is determined based on the sum of the associated values ​​Z in each historical fault information.

[0124] Furthermore, when the assignment module a assigns a value to the weight X;

[0125] The attribution of failure factors includes internal factors or external factors;

[0126] When the fault factor is attributed to an internal factor, the value of weight X is 1;

[0127] When the fault factor is classified as an external factor, each fault cause is classified into the first, second, third and fourth categories of factors according to the difficulty of solving the fault from easy to difficult; the weight X assigned to all fault causes in the first category of factors is 0, the weight X assigned to all fault causes in the second category of factors is 0.2, the weight X assigned to all fault causes in the third category of factors is 0.4, and the weight X assigned to all fault causes in the fourth category of factors is 0.7.

[0128] Further, when the weight assignment module b assigns a value to the weight Y,;

[0129] Multiple base stations in the same area are classified into Class A base stations, Class B base stations, Class C base stations and Class D base stations in order of value from high to low, among which the weight Y assigned to all base stations in Class A base stations is 0.8, the weight Y assigned to all base stations in Class B base stations is 0.6, the weight Y assigned to all base stations in Class C base stations is 0.4, and the weight Y assigned to all base stations in Class D base stations is 0.2.

[0130] Furthermore, when calculating the fault severity index, the fault severity index calculation module:

[0131] According to the weight X corresponding to the cause of the fault and the weight Y corresponding to the base station where the fault occurs, the fault severity index of the base station is calculated. The calculation formula is:

[0132] Z=X*Y

[0133] Wherein, Z represents the fault severity index of the base station.

[0134] Furthermore, it also includes an immune index calculation module;

[0135] The immune index calculation module can determine the immune index of the base station when encountering a fault based on the weight X, weight Y and factor attribution. The immune index represents the immune ability of different base stations in dealing with different faults.

[0136] The immune de-service duration of the base station is determined based on the immune index and the base station de-service duration. The immune de-service duration represents the degree of impact of different base stations on surrounding areas under different faults.

[0137] Furthermore, when the immune index calculation module is calculating the immune index:

[0138] When the factor is attributed to internal factors, the immunity index is 1;

[0139] When the factor is classified as an external factor and belongs to a category of factors, the immunity index is 0;

[0140] When the factor is classified as an external factor and belongs to the second, third or fourth category, the calculation equation of the immunity index is:

[0141] U=Y(1-X)

[0142] Among them, U is the immune index;

[0143] The system also includes an immune withdrawal time calculation module, in which:

[0144] The immune service withdrawal time calculation module can determine the base station immune service withdrawal time according to the immune index and the base station service withdrawal time. The calculation formula is:

[0145] T=t*U

[0146] Among them, T represents the base station immune decommissioning time, and t represents the base station decommissioning time.

[0147] The present invention also provides a computer-readable medium, in which instructions are stored. When the instructions are executed on a terminal device, the terminal device executes the steps of the above-mentioned fault decision method based on the immune algorithm.

[0148] The present invention also provides an electronic device, comprising a memory, a processor and a program stored in the memory and running on the processor, characterized in that when the processor executes the program, the steps of the fault decision method based on the immune algorithm are implemented.

[0149] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A fault decision method based on immune algorithm, characterized in that: include: Establishing a database, the database including a plurality of base station data, each of the base station data including a plurality of historical fault information, each of the historical fault information including a plurality of first keywords corresponding to the fault and a cause of the fault; Assigning different weights X to each of the causes in accordance with the standards, wherein the standards include the difficulty of troubleshooting and the attribution of the fault factors; Assign different weights Y from large to small to multiple base stations according to their values ​​from high to low; When a base station fails, a new complaint work order is obtained, wherein the new complaint work order contains multiple second keywords; for each of the second keywords, the cause of the new complaint work order is determined according to the distribution of the first keyword that is the same as the second keyword in different historical fault information; Calculate the fault severity index of the base station according to the weight X corresponding to the cause and the weight Y corresponding to the base station where the fault occurs; According to the fault severity index, deciding resource allocation corresponding to the faulty base station; For each of the second keywords, determining the generation cause corresponding to the new complaint work order according to the distribution of the first keyword identical to the second keyword in different historical fault information, including: In each of the fault information, assigning a correlation value Z to each of the first keywords according to the correlation between each of the first keywords and the cause; respectively counting the sum of the association values ​​Z of the plurality of the first keywords that are the same as the plurality of the second keywords in each of the historical fault information; Determine the historical fault information corresponding to the maximum sum of the correlation values ​​Z, and obtain the generation cause in the historical fault information as the generation cause corresponding to the new complaint work order; The fault factor attribution includes internal factors or external factors, and each of the causes is assigned different weights X in turn according to the standard, including: When the fault factor is classified as an internal factor, the value of the weight X is 1; When the fault factor is classified as an external factor, each fault cause is classified into the first category, second category, third category and fourth category factors in order of difficulty of solving the fault from easy to difficult; the weight X assigned to all the fault causes in the first category is 0, the weight X assigned to all the fault causes in the second category is 0.2, the weight X assigned to all the fault causes in the third category is 0.4, and the weight X assigned to all the fault causes in the fourth category is 0.7; Assign different weights Y from large to small to multiple base stations according to their values ​​from high to low, including: Classify multiple base stations into Class A base stations, Class B base stations, Class C base stations and Class D base stations in order of value from high to low, wherein the weight Y assigned to all base stations in the Class A base stations is 0.8, the weight Y assigned to all base stations in the Class B base stations is 0.6, the weight Y assigned to all base stations in the Class C base stations is 0.4, and the weight Y assigned to all base stations in the Class D base stations is 0.2; According to the weight X corresponding to the cause of the fault, combined with the weight Y corresponding to the base station where the fault occurs, the fault severity index of the base station is calculated, and the calculation formula is: Z=X*Y Wherein, Z represents the fault severity index of the base station.

2. The fault decision method based on immune algorithm according to claim 1, characterized in that: It also includes: determining the immunity index of the base station when encountering a fault according to the weight X, weight Y and factor attribution corresponding to the cause, wherein the immunity index represents the immunity capability of different base stations in dealing with different faults; The immune de-service duration of the base station is determined according to the immune index and the base station de-service duration, wherein the immune de-service duration represents the degree of influence of different base stations on surrounding areas under different faults.

3. The fault decision method based on immune algorithm according to claim 2 is characterized in that: When the factor is classified as an internal factor, the immune index is 1; When the factor is classified as an external factor and belongs to a category of factors, the immunity index is 0; When the factor is classified as an external factor and belongs to the second, third or fourth category factors, the calculation equation of the immune index is: U=Y(1-X) Wherein, U is the immune index; According to the immune index and the base station decommissioning time, the base station immune decommissioning time is determined, and the calculation formula is: T=t*U Wherein, T represents the base station immune de-service duration, and t represents the base station de-service duration.

4. The fault decision system based on immune algorithm is characterized by: include: A data storage module, wherein the data storage module has a database, wherein the database includes a plurality of base station data, each of the base station data includes a plurality of historical fault information, and each of the historical fault information includes a plurality of first keywords corresponding to the fault and a corresponding cause of occurrence; The weight assignment module a assigns different weights X to each of the causes in the data storage module in accordance with the standard, wherein the standard includes the difficulty of troubleshooting and the attribution of the fault factors; The weight assignment module b assigns different weights Y from large to small to multiple base stations in the database according to their values ​​from high to low; A fault cause judgment module, when a base station fails, obtains a new complaint work order, wherein the new complaint work order contains multiple second keywords; for each of the second keywords, the cause of the new complaint work order is determined according to the distribution of the first keyword that is the same as the second keyword in different historical fault information; A fault severity index calculation module calculates the fault severity index of the base station according to the weight X corresponding to the cause and the weight Y corresponding to the base station where the fault occurs; A decision module, which decides resource allocation of a corresponding faulty base station according to the fault severity index; When the fault cause judgment module is analyzing the cause of the base station fault: In each fault information, a different correlation value Z is assigned to each first keyword according to the correlation between each first keyword and the cause of the fault; For each second keyword, sequentially calculate the association value Z of the first keyword that is the same as the second keyword in different historical fault information; Determine the cause of the fault according to the sum of the associated values ​​Z in each historical fault information; When the assignment module a assigns a value to the weight X; The attribution of failure factors includes internal factors or external factors; When the fault factor is attributed to an internal factor, the value of weight X is 1; When the fault factor is classified as an external factor, each fault cause is classified into the first, second, third and fourth categories of factors according to the difficulty of solving the fault from easy to difficult; the weight X assigned to all fault causes in the first category of factors is 0, the weight X assigned to all fault causes in the second category of factors is 0.2, the weight X assigned to all fault causes in the third category of factors is 0.4, and the weight X assigned to all fault causes in the fourth category of factors is 0.7; When the weight assignment module b assigns a value to the weight Y; Multiple base stations in the same area are classified into Class A base stations, Class B base stations, Class C base stations and Class D base stations according to their values ​​from high to low, wherein the weight Y assigned to all base stations in Class A base stations is 0.8, the weight Y assigned to all base stations in Class B base stations is 0.6, the weight Y assigned to all base stations in Class C base stations is 0.4, and the weight Y assigned to all base stations in Class D base stations is 0.2; When calculating the fault severity index, the fault severity index calculation module: According to the weight X corresponding to the cause of the fault and the weight Y corresponding to the base station where the fault occurs, the fault severity index of the base station is calculated. The calculation formula is: Z=X*Y Wherein, Z represents the fault severity index of the base station.

5. A computer-readable medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed on the terminal device, the terminal device executes the steps of the fault decision method based on the immune algorithm as described in any one of claims 1 to 3.

6. An electronic device comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the steps of the fault decision method based on the immune algorithm as described in any one of claims 1 to 3 are implemented.

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