A Communication Base Station Data Interaction Supervision Method and System Based on Data Interaction

Abstract

The present invention relates to the field of data management, and specifically to a communication base station data interaction supervision method and system based on data interaction. The system includes an abnormal operation state category set construction module, a real-time communication base station operation data acquisition module, a communication base station real-time operation state determination module, an abnormal operation state category matching module, a solution optimization module, and an abnormal operation state processing module. The real-time operation state of the communication base station is determined through the real-time communication base station operation data set. When an abnormal operation state occurs, the real-time communication base station operation data set is matched with the abnormal operation state category set, and the abnormal operation state category is found according to the matching result to find the optimal solution for regulation and maintenance, avoiding unnecessary consumption of human resources and realizing the safety supervision of the communication base station at the same time. The optimization process of the solution is realized through the krill herd algorithm, which improves the speed and accuracy of the optimization process and enhances the efficiency of the convergence process.

Description

Technical Field

[0001] The present invention relates to the field of data management, and specifically to a communication base station data interaction supervision method and system based on data interaction. Background Art

[0002] With the rapid development of wireless communication technology, communication base stations play an increasingly crucial role in wireless communication networks. Therefore, the scale of communication base stations is constantly expanding, bringing communication convenience while also increasing the difficulty of managing and detecting communication base stations.

[0003] In the prior art, communication base stations often install communication base station management systems provided by equipment manufacturers, and collect operation data through sensors and upload it to the cloud platform for supervision. However, the feedback and maintenance of many of the information still need to be realized manually, which not only increases labor costs, but also cannot analyze the reasons for the occurrence of abnormal situations, cannot provide quick and effective help for abnormal situations, and it is difficult to achieve modern and intelligent supervision of communication base stations. Summary of the Invention

[0004] (1) Technical Problems to be Solved

[0005] To solve the deficiencies in the background art, the present invention proposes a communication base station data interaction supervision method and system based on data interaction. By determining the real-time operation status of a communication base station through real-time communication base station operation data sets, when an abnormal operation status occurs, the real-time communication base station operation data set is matched with the abnormal operation status category set, and the optimal solution is found according to the matching result to feedback the abnormal operation status category, and regulation and maintenance are carried out to achieve the safety supervision of the communication base station.

[0006] (2) Technical Solutions

[0007] A communication base station data interaction supervision method based on data interaction, the method includes the following steps:

[0008] S1. Collect abnormal operation status data in historical data, cluster the abnormal operation status data by using the agglomerative hierarchical clustering algorithm, and establish an abnormal operation status category set according to each cluster of abnormal operation status data obtained after clustering;

[0009] S2. Set a communication base station operation data category set, and collect in real time the communication base station operation data of each communication base station operation data category in the communication base station operation data category set to obtain a real-time communication base station operation data set;

[0010] S3. Feed the real-time communication base station operation data set back to the communication base station operation status monitoring unit to determine the real-time operation status of the communication base station;

[0011] S4. When the determination result of the real-time operating state of the communication base station is an abnormal operating state, match the real-time communication base station operation data set with each abnormal operating state category in the abnormal operating state category set one by one, and feedback the matching result to the communication base station operation state management unit and issue an alarm;

[0012] S5. The communication base station operation state management unit finds the optimal solution according to the matching result;

[0013] S6. The operation and maintenance personnel issue corresponding operation instructions to the communication base station abnormal operating state processing unit according to the optimal solution.

[0014] By clustering the collected abnormal operating state data, an abnormal operating state category set is established, ensuring the comprehensiveness and accuracy of the acquired data; by analyzing the numerical size of the collected real-time communication base station operation data to determine whether it is within the range of the normal state operation data of the corresponding communication base station, the real-time operating state of the communication base station is determined, ensuring the reliability of the determination result; the real-time communication base station operation data set is matched with the abnormal operating state category set, and the corresponding abnormal operating state category is fed back according to the matching result to realize the determination of the abnormal operating state category; the operation and maintenance personnel take corresponding operation instructions according to the optimal solution to regulate the equipment in the communication base station, and judge whether to perform the next operation according to whether the alarm is lifted, realizing the safety supervision of the communication base station while avoiding unnecessary consumption of human resources.

[0015] Preferably, collect the abnormal operating state data in the historical data, use the agglomerative hierarchical clustering algorithm to cluster the abnormal operating state data, and the specific steps to establish the abnormal operating state category set according to each cluster of abnormal operating state data obtained after clustering are as follows:

[0016] S11. Collect the abnormal operating state data in the historical data, regard each abnormal operating state data as a cluster, calculate the Euclidean distance between clusters, and obtain a distance matrix;

[0017] S12. Find the two clusters with the closest Euclidean distance from the distance matrix and merge them into a new cluster, and calculate the Euclidean distance between the new cluster and other clusters;

[0018] S13. Repeat S11 and S12 until the Euclidean distance between each cluster obtained after clustering is greater than the set Euclidean distance threshold, then stop clustering, and establish the abnormal operating state category set A=(a1, a2, …, a i , …, a k ) according to each cluster of abnormal operating state data obtained after clustering, where a i represents the i-th abnormal operating state category, and k represents the total number of abnormal operating state categories.

[0019] The abnormal operation state data collected are clustered by the agglomerative hierarchical clustering algorithm to establish a set of abnormal operation state categories, ensuring the comprehensiveness and accuracy of the acquired data and providing a data basis for the subsequent matching process.

[0020] Preferably, the steps for setting a set of communication base station operation data categories and collecting in real time the communication base station operation data of each communication base station operation data category in the set of communication base station operation data categories to obtain a real-time communication base station operation data set are as follows:

[0021] S21. Set a set of communication base station operation data categories B=(b1, b2,..., b i ,..., b l ), where b i represents the i-th communication base station operation data category, and l represents the total number of communication base station operation data categories;

[0022] S22. Through a data acquisition device, collect in real time the communication base station operation data of each communication base station operation data category in the set of communication base station operation data categories B=(b1, b2,..., b i ,…, b l ) to obtain a real-time communication base station operation data set B'=(b'1, b'2,…, b' i ,…, b' l ), where b' i represents the real-time communication base station operation data corresponding to the i-th communication base station operation data category.

[0023] By setting a set of communication base station operation data categories and collecting in real time the communication base station operation data of each communication base station operation data category, the comprehensiveness of the collected data is ensured, providing a data basis for subsequent operations.

[0024] Preferably, the steps for feeding back the real-time communication base station operation data set to a communication base station operation state monitoring unit to determine the real-time operation state of the communication base station are as follows:

[0025] S31. Set a range interval set of communication base station normal state operation data where and respectively represent the minimum value and the maximum value of the normal state operation data of the i-th communication base station operation data category;

[0026] S32. After the communication base station operation status monitoring unit receives the feedback real-time communication base station operation data set, it sequentially determines whether the numerical values of each real-time communication base station operation data in the real-time communication base station operation data set are within the corresponding communication base station normal state operation data range interval in the communication base station normal state operation data range interval set. If the numerical values of all real-time communication base station operation data are within the corresponding communication base station normal state operation data range interval, it is determined that the real-time operation status of the communication base station is the normal operation status; otherwise, it is determined that the real-time operation status of the communication base station is the abnormal operation status.

[0027] By setting the communication base station normal state operation data range interval set and analyzing the numerical values of the collected real-time communication base station operation data, the real-time operation status of the communication base station is determined, ensuring the reliability of the determination result.

[0028] Preferably, when the determination result of the real-time operation status of the communication base station is the abnormal operation status, the specific steps of matching the real-time communication base station operation data set with each abnormal operation status category in the abnormal operation status category set one by one, feeding back the matching result to the communication base station operation status management unit and issuing an alarm are as follows:

[0029] S41. When the determination result of the real-time operation status of the communication base station is the abnormal operation status, match the real-time communication base station operation data set with each abnormal operation status category in the abnormal operation status category set one by one; the matching process is as follows:

[0030] S411. Construct a planet population, set the maximum number of iterations t max and the population size l;

[0031] Regard each abnormal operation status category in the abnormal operation status category set A=(a1,a2,…,a i ,…,a k ) as a planet individual, and randomly generate an initial position set of l planet individuals in the search space where, represents the initial position of the i-th planet individual;

[0032] S412. Calculate the fitness function value of each planet individual in the planet population, compare the fitness function values of all planet individuals, and select the planet individual with the largest fitness function value as the black hole; the fitness function formula is as follows:

[0033]

[0034] where, x i represents the matching degree between the i-th abnormal operation status category and the real-time communication base station operation data in the real-time communication base station operation data set, and λ represents the correction value;

[0035] S413. After the position of the black hole is determined, all non-black-hole planet individuals will be affected by the gravitational force of the black hole and move towards the black hole along a certain trajectory. The position update formula for the planet moving towards the black hole is as follows:

[0036]

[0037] Wherein, and respectively represent the positions of the i-th planet individual in the (t + 1)-th and t-th iteration processes. rand represents a random number between (0, 1), and x BH represents the position of the black hole;

[0038] S414. Calculate the fitness function value of the new position reached by each planet individual after position update. If the fitness function value of the new position is higher than the fitness function value of the black hole position, then this planet individual replaces the previous black hole to become the new black hole, and the previous black hole reverts to a planet and moves towards the new black hole;

[0039] S415. Under the gravitational force of the black hole, the planet will continuously approach the black hole. When the distance between a planet and the black hole is less than the distance threshold R(t), the planet will be absorbed by the black hole, and at the same time, a new planet individual will be randomly generated in the search space. The calculation formula for the distance threshold is as follows:

[0040]

[0041] Wherein, Fit(x BH ) represents the fitness function value of the black hole, represents the fitness function value of the i-th planet individual in the t-th iteration process;

[0042] S416. Determine whether the maximum number of iterations t max is reached. If not, return to S413; if so, take the black hole as the current global optimal solution, set the fitness function threshold Fit 阈值 . When the fitness function value of the black hole is greater than the fitness function threshold Fit 阈值 , then the abnormal operation state category corresponding to the current global optimal solution matches successfully with the real-time communication base station operation data set; otherwise, the real-time communication base station operation data fails to match with each abnormal operation state category in the abnormal operation state category set;

[0043] S42. If the match is successful, then feedback the abnormal operation state category that matches successfully with the real-time communication base station operation data set to the communication base station operation state management unit and issue an alarm;

[0044] If the real-time communication base station operation data set fails to match all the abnormal operation status categories in the abnormal operation status category set, a new abnormal operation status category is set for the real-time communication base station operation data set and stored in the abnormal operation status category set. At the same time, the abnormal operation status category is fed back to the communication base station operation status management unit and an alarm is issued.

[0045] The matching process between the real-time communication base station operation data set and the abnormal operation status category set is realized through the black hole algorithm. By using the phenomenon that a planet will move towards the black hole under the gravitational force of the black hole, a mathematical model is constructed, which ensures the accuracy of the matching result and speeds up the matching process. According to the matching result, the corresponding abnormal operation status category is fed back to realize the determination of the abnormal operation status category.

[0046] Preferably, the specific steps for the communication base station operation status management unit to find the optimal solution according to the matching result are as follows:

[0047] S51. Construct a krill population, set the current iteration number as T, the maximum iteration number as T max , the population size as N, the maximum induced movement speed as N max , the induced weight as ω n , the maximum foraging movement speed as V f , the foraging weight as ω f , the maximum random diffusion movement speed as D max and the movement period of the krill individual as Δt;

[0048] Initialize the initial position set of the krill population as Y = {y1, y2, …, y i , …, y N}, where y i represents the initial position of the i-th krill individual in the krill population;

[0049] S52. Calculate the fitness function value of each krill individual in the krill population, and take the krill individual with the highest fitness as the current optimal krill individual; the fitness function formula is as follows:

[0050]

[0051] where y i represents the ability of the i-th krill individual in the krill population to solve the abnormal operation status, and μ represents the correction value;

[0052] S53. Calculate the movement speed of the krill individual according to the influence of the krill individual being induced, foraging, and randomly diffusing; the calculation formula is as follows:

[0053]

[0054] where, represents the movement speed of the \(i\)-th krill individual, \(N\) i represents the induced movement speed of the \(i\)-th krill individual, \(F\) i represents the foraging movement speed of the \(i\)-th krill individual, \(D\) i represents the random diffusion movement speed of the \(i\)-th krill individual;

[0055] S531. The krill individuals in the krill population will be induced by the nearby krill individuals and the optimal krill individuals to move; the formula for the induced movement speed is as follows:

[0056]

[0057] where, and respectively represent the induced movement speeds of the \(i\)-th krill individual in the \((T + 1)\)-th and \(T\)-th iteration processes, \(\alpha\) i local and \(\alpha\) i target respectively represent the induced speeds of the \(i\)-th krill individual by the adjacent krill and the current optimal krill individual;

[0058] S532. The krill individuals in the krill population will forage according to the food position and previous foraging experience; the formula for the foraging movement speed is as follows:

[0059]

[0060] where, \(F\) i T+1 and \(F\) i T respectively represent the foraging movement speeds of the \(i\)-th krill individual in the \((T + 1)\)-th and \(T\)-th iteration processes, \(\beta\) i food and \(\beta\) i best respectively represent the attractions of the \(i\)-th krill individual to the food and its own historical optimal individual;

[0061] S533. The krill individuals in the krill population will perform random diffusion according to the maximum diffusion speed and the randomly selected moving direction; the formula for the random diffusion movement speed is as follows:

[0062]

[0063] where, represents the random diffusion movement speed of the \(i\)-th krill individual in the \(T\)-th iteration process, \(D\) max represents the maximum random diffusion movement speed, \(\delta\) represents the randomly selected diffusion direction;

[0064] S54. Update the position of each krill individual according to the movement speed of each krill individual in the krill population; the position update formula is as follows:

[0065]

[0066] Among them, y i (t) represents the position of the krill individual at time t;

[0067] S55, for each krill individual in the krill population, randomly select other krill individuals according to the set crossover probability to perform a crossover operation to generate new krill individuals;

[0068] S56, performing a mutation operation on each krill individual in the krill population according to a set mutation probability to generate a new krill individual;

[0069] S57, calculating the fitness function values ​​of all krill individuals after position update and new krill individuals generated after crossover and mutation operations, arranging them from large to small according to the fitness function values, and selecting N krill individuals with the highest fitness function values ​​as the new krill population;

[0070] S58, determine whether the maximum number of iterations T is reached max If it is not reached, return to S53; if it is reached, the krill individual with the highest fitness function value is taken as the global optimal solution, and the solution corresponding to the global optimal solution is output as the optimal solution.

[0071] In the process of finding the optimal solution through the krill swarm optimization algorithm, a mathematical model is constructed using the laws of movement and mutation of krill swarms in nature to improve the speed and accuracy of the optimization process and the efficiency of the convergence process.

[0072] Preferably, the specific steps for the operation and maintenance personnel to issue corresponding operation instructions to the abnormal operation status processing unit of the communication base station according to the optimal solution are as follows:

[0073] S61. The operation and maintenance personnel issue corresponding operation instructions to the abnormal operation state processing unit of the communication base station according to the optimal solution output by the communication base station operation state management unit, and regulate the equipment in the communication base station;

[0074] S611, if the alarm is relieved after the equipment is regulated, the operation is terminated;

[0075] If the alarm is not lifted after equipment adjustment, the operation and maintenance personnel will feedback the real-time communication base station operation data and the corresponding abnormal operation status category to the on-site engineer, and the on-site engineer will perform further adjustment and maintenance based on the real-time communication base station operation data and the corresponding abnormal operation status category.

[0076] The operation and maintenance personnel take corresponding operation instructions according to the optimal solution to regulate the equipment in the communication base station, and judge whether to perform the next operation according to whether the alarm is lifted, realizing the safety supervision of the communication base station while avoiding unnecessary consumption of human resources.

[0077] The present invention also discloses a system for a communication base station data interaction supervision method based on data interaction, including an abnormal operation state category set construction module, a real-time communication base station operation data acquisition module, a communication base station real-time operation state determination module, an abnormal operation state category matching module, a solution optimization module, and an abnormal operation state processing module;

[0078] The abnormal operation state category set construction module clusters the collected abnormal operation state data through an agglomerative hierarchical clustering algorithm, and establishes an abnormal operation state category set according to the clustering result;

[0079] The real-time communication base station operation data acquisition module obtains a real-time communication base station operation data set by real-time collecting the communication base station operation data of each communication base station operation data category in the set of communication base station operation data categories set;

[0080] The communication base station real-time operation state determination module determines the real-time operation state of the communication base station by analyzing whether the numerical values of all real-time communication base station operation data are within the range of the normal state operation data of the communication base station corresponding to the communication base station operation data category;

[0081] The abnormal operation state category matching module matches the real-time communication base station operation data set with each abnormal operation state category in the abnormal operation state category set one by one through a black hole algorithm;

[0082] The solution optimization module finds an optimal solution for the matching result in the communication base station operation state management unit through a krill herd optimization algorithm;

[0083] The abnormal operation state processing module enables the operation and maintenance personnel to send corresponding operation instructions to the communication base station abnormal operation state processing unit according to the optimal solution, regulate the equipment in the communication base station, and perform corresponding next operations according to whether the alarm is lifted.

[0084] (III) Advantageous Effects

[0085] The present invention provides a communication base station data interaction supervision method and system based on data interaction, having the following advantageous effects:

[0086] 1. In the present invention, an abnormal operation status category set construction module, a real-time communication base station operation data collection module, a communication base station real-time operation status determination module, an abnormal operation status category matching module, a solution optimization module, and an abnormal operation status processing module are provided. By clustering the collected abnormal operation status data, an abnormal operation status category set is established, ensuring the comprehensiveness and accuracy of the acquired data. By analyzing the numerical magnitude of the collected real-time communication base station operation data to determine whether it is within the range of the normal operation data of the corresponding communication base station, the real-time operation status of the communication base station is determined, ensuring the reliability of the determination result. The operation and maintenance personnel take corresponding operation instructions according to the optimal solution to regulate the equipment in the communication base station, and judge whether to perform the next operation according to whether the alarm is lifted, realizing the safety supervision of the communication base station while avoiding unnecessary consumption of human resources.

[0087] 2. The matching process between the real-time communication base station operation data set and the abnormal operation status category set is realized through the black hole algorithm. By using the phenomenon that a planet will move towards the black hole under the gravitational force of the black hole, a mathematical model is constructed, ensuring the accuracy of the matching result and accelerating the speed of the matching process.

[0088] 3. The process of finding the optimal solution according to the matching result is realized through the krill herd optimization algorithm. By using the laws of movement and mutation of the krill herd in nature, a mathematical model is constructed, improving the speed and accuracy of the optimization process and enhancing the efficiency of the convergence process. BRIEF DESCRIPTION OF THE DRAWINGS

[0089] In order to more clearly illustrate the technical solutions of the embodiments of the invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0090] Figure 1 It is a flowchart of a communication base station data interaction supervision method based on data interaction provided by the present invention.

[0091] Figure 2 It is a schematic diagram of the modules of a system of a communication base station data interaction supervision method based on data interaction provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0092] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0093] In the description of the present invention, it should be understood that the terms "opening", "upper", "lower", "top", "middle", "inner", etc. indicating orientation or positional relationships are only for the convenience of describing the invention and simplifying the description, rather than indicating or implying that the components or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the invention.

[0094] The first embodiment of the communication base station data interaction supervision method and system based on data interaction is as follows:

[0095] Please refer to Figure 1 , a communication base station data interaction supervision method based on data interaction, comprising the following steps:

[0096] S1. Collect the abnormal operation state data in the historical data, cluster the abnormal operation state data by using the agglomerative hierarchical clustering algorithm, and establish an abnormal operation state category set according to the various abnormal operation state data clusters obtained after clustering;

[0097] S11. Collect the abnormal operation state data in the historical data, regard each abnormal operation state data as a cluster, calculate the Euclidean distance between clusters, and obtain a distance matrix;

[0098] S12. Find the two clusters with the closest Euclidean distance from the distance matrix, merge them into a new cluster, and calculate the Euclidean distance between the new cluster and other clusters;

[0099] S13. Repeat S11 and S12 until the Euclidean distance between each cluster obtained after clustering is greater than the set Euclidean distance threshold, then stop clustering, and establish an abnormal operation state category set A = (a1, a2,..., a i ,..., a k ), where a i represents the i-th abnormal operation state category, and k represents the total number of abnormal operation state categories.

[0100] S2. Set a communication base station operation data category set, and collect the communication base station operation data of each communication base station operation data category in the communication base station operation data category set in real time to obtain a real-time communication base station operation data set;

[0101] S21. Set a communication base station operation data category set B = (b1, b2,..., b i ,..., b l ), where b i represents the i-th communication base station operation data category, and l represents the total number of communication base station operation data categories;

[0102] S22. Real - time collect the communication base station operation data of each communication base station operation data category in the communication base station operation data category set B=(b1, b2, …, b i , …, b l ) through the data collection device, and obtain the real - time communication base station operation data set B'=(b'1, b'2, …, b' i , …, b' l ), where b' i represents the real - time communication base station operation data corresponding to the i - th communication base station operation data category.

[0103] S3. Feed back the real - time communication base station operation data set to the communication base station operation status monitoring unit to determine the real - time operation status of the communication base station;

[0104] S31. Set the communication base station normal - state operation data range interval set where, and respectively represent the minimum value and the maximum value of the normal - state operation data of the i - th communication base station operation data category;

[0105] S32. After the communication base station operation status monitoring unit receives the fed - back real - time communication base station operation data set, sequentially determine whether the numerical values of each real - time communication base station operation data in the real - time communication base station operation data set are within the corresponding communication base station normal - state operation data range interval in the communication base station normal - state operation data range interval set. If the numerical values of all real - time communication base station operation data are within the corresponding communication base station normal - state operation data range interval, then determine that the real - time operation status of the communication base station is the normal operation status; otherwise, determine that the real - time operation status of the communication base station is the abnormal operation status.

[0106] S4. When the determination result of the real - time operation status of the communication base station is the abnormal operation status, match the real - time communication base station operation data set with each abnormal operation status category in the abnormal operation status category set one by one, and feed back the matching result to the communication base station operation status management unit and issue an alarm;

[0107] S41. When the determination result of the real - time operation status of the communication base station is the abnormal operation status, match the real - time communication base station operation data set with each abnormal operation status category in the abnormal operation status category set one by one. The matching process is as follows:

[0108] S411. Construct a planetary population, set the maximum number of iterations t max and the population size l;

[0109] Match the abnormal operation status category set A=(a1, a2,..., a i ,..., a k) Each abnormal operating state category in it is regarded as a planet individual, and an initial position set of l planet individuals is randomly generated in the search space Among them, represents the initial position of the i-th planet individual;

[0110] S412. Calculate the fitness function value of each planet individual in the planet population, compare the fitness function values of all planet individuals, and select the planet individual with the largest fitness function value as the black hole. The fitness function formula is as follows:

[0111]

[0112] Among them, x i represents the matching degree between the i-th abnormal operating state category and the real-time communication base station operation data in the real-time communication base station operation data set, and λ represents the correction value;

[0113] S413. When the position of the black hole is determined, all non-black hole planet individuals will be affected by the gravitational force of the black hole and move towards the black hole direction along a certain trajectory. The position update formula for the planet to move towards the black hole is as follows:

[0114]

[0115] Among them, and respectively represent the positions of the i-th planet individual in the (t + 1)-th and t-th iteration processes, rand represents a random number between (0, 1), and x BH represents the position of the black hole;

[0116] S414. Calculate the fitness function value of the new position reached by each planet individual after position update. If the fitness function value of the new position is higher than the fitness function value of the black hole position, then this planet individual replaces the previous black hole to become the new black hole, and the previous black hole becomes a planet again and moves towards the new black hole;

[0117] S415. Under the gravitational force of the black hole, the planet will continuously approach the black hole. When the distance between a planet and the black hole is less than the distance threshold R(t), the planet will be absorbed by the black hole, and at the same time, a planet individual is randomly generated again in the search space. The calculation formula for the distance threshold is as follows:

[0118]

[0119] Among them, Fit(x BH ) represents the fitness function value of the black hole, represents the fitness function value of the i-th planet individual in the t-th iteration process;

[0120] S416. Determine whether the maximum number of iterations t is reached max , if not, return to S413; if so, take the black hole as the current global optimal solution and set the fitness function threshold Fit 阈值 , when the fitness function value of the black hole is greater than the fitness function threshold Fit 阈值 , then the abnormal operation state category corresponding to the current global optimal solution is successfully matched with the real-time communication base station operation data set; otherwise, the real-time communication base station operation data fails to match with each abnormal operation state category in the abnormal operation state category set;

[0121] S42. If the match is successful, feedback the abnormal operation state category that is successfully matched with the real-time communication base station operation data set to the communication base station operation state management unit and issue an alarm;

[0122] If the real-time communication base station operation data set fails to match with each abnormal operation state category in the abnormal operation state category set, set a new abnormal operation state category for the real-time communication base station operation data set and store it in the abnormal operation state category set, and at the same time feedback the abnormal operation state category to the communication base station operation state management unit and issue an alarm.

[0123] S5. The communication base station operation state management unit finds the optimal solution according to the matching result;

[0124] S51. Construct a krill population, set the current iteration number as T, the maximum iteration number as T max , the population size as N, the maximum induced movement speed as N max , the induced weight as ω n , the maximum foraging movement speed as V f , the foraging weight as ω f , the maximum random diffusion movement speed as D max and the movement period of the krill individual as Δt;

[0125] Initialize the initial position set of the krill population as Y = {y1, y2, …, y i , …, y N}, where y i represents the initial position of the i-th krill individual in the krill population;

[0126] S52. Calculate the fitness function value of each krill individual in the krill population, and take the krill individual with the highest fitness as the current optimal krill individual; the fitness function formula is as follows:

[0127]

[0128] Among them, y irepresents the ability of the \(i\)-th krill individual in the krill population to solve abnormal operating states, and \(\mu\) represents the correction value;

[0129] S53. Calculate the movement speed of the krill individual according to the influence of induction, foraging, and random diffusion of the krill individual. The calculation formula is as follows:

[0130]

[0131] Among them, represents the movement speed of the \(i\)-th krill individual, \(N\) i represents the induced movement speed of the \(i\)-th krill individual, \(F\) i represents the foraging movement speed of the \(i\)-th krill individual, \(D\) i represents the random diffusion movement speed of the \(i\)-th krill individual;

[0132] S531. The krill individuals in the krill population will be induced to move by the nearby krill individuals and the optimal krill individual. The induced movement speed formula is as follows:

[0133]

[0134] Among them, and respectively represent the induced movement speeds of the \(i\)-th krill individual in the \((T + 1)\)-th and \(T\)-th iteration processes, \(\alpha\) i local and \(\alpha\) i target respectively represent the induced directions of the \(i\)-th krill individual by the adjacent krill and the current optimal krill individual, \(\alpha\) i represents the induced direction of the \(i\)-th krill individual;

[0135] S532. The krill individuals in the krill population will forage according to the food position and previous foraging experience. The foraging movement speed formula is as follows:

[0136]

[0137] Among them, \(F\) i T+1 and \(F\) i T respectively represent the foraging movement speeds of the \(i\)-th krill individual in the \((T + 1)\)-th and \(T\)-th iteration processes, \(\beta\) i food and \(\beta\) i best respectively represent the attractions of the \(i\)-th krill individual by the food and the individual's own historical optimal individual, \(\beta\) i represents the foraging direction of the \(i\)-th krill individual;

[0138] S533. Krill individuals in a krill population will diffuse randomly according to the maximum diffusion speed and the randomly selected movement direction. The formula for the random diffusion movement speed is as follows:

[0139]

[0140] in, represents the random diffusion speed of the i-th krill individual during the T-th iteration, D max represents the maximum random diffusion motion speed, and δ represents the randomly selected diffusion direction;

[0141] S54. Update the position of each krill individual according to the movement speed of each krill individual in the krill population. The position update formula is as follows:

[0142]

[0143] Among them, y i (t) represents the position of the krill individual at time t;

[0144] S55, for each krill individual in the krill population, randomly select other krill individuals according to the set crossover probability to perform a crossover operation to generate new krill individuals;

[0145] S56, performing a mutation operation on each krill individual in the krill population according to a set mutation probability to generate a new krill individual;

[0146] S57, calculating the fitness function values ​​of all krill individuals after position update and new krill individuals generated after crossover and mutation operations, arranging them from large to small according to the fitness function values, and selecting N krill individuals with the highest fitness function values ​​as the new krill population;

[0147] S58, determine whether the maximum number of iterations T is reached max If it is not reached, return to S53; if it is reached, the krill individual with the highest fitness function value is taken as the global optimal solution, and the solution corresponding to the global optimal solution is output as the optimal solution.

[0148] S6. The operation and maintenance personnel issue corresponding operation instructions to the abnormal operation status processing unit of the communication base station according to the optimal solution;

[0149] S61. The operation and maintenance personnel issue corresponding operation instructions to the abnormal operation state processing unit of the communication base station according to the optimal solution output by the communication base station operation state management unit, and regulate the equipment in the communication base station;

[0150] S611, if the alarm is relieved after the equipment is regulated, the operation is terminated;

[0151] If the alarm is not lifted after equipment adjustment, the operation and maintenance personnel will feedback the real-time communication base station operation data and the corresponding abnormal operation status category to the on-site engineer, and the on-site engineer will perform further adjustment and maintenance based on the real-time communication base station operation data and the corresponding abnormal operation status category.

[0152] The second embodiment of the communication base station data interaction supervision method and system based on data interaction is as follows:

[0153] See also Figure 2 , a system for a data interaction supervision method of a communication base station based on data interaction includes an abnormal operation status category set construction module, a real-time communication base station operation data collection module, a communication base station real-time operation status determination module, an abnormal operation status category matching module, a solution optimization module, and an abnormal operation status processing module;

[0154] The abnormal operation status category set building module clusters the collected abnormal operation status data by using an agglomerative hierarchical clustering algorithm, and establishes an abnormal operation status category set according to the clustering result;

[0155] The real-time communication base station operation data collection module obtains a real-time communication base station operation data set by collecting the communication base station operation data of each communication base station operation data category in the set communication base station operation data category set in real time;

[0156] The communication base station real-time operation status determination module determines the real-time operation status of the communication base station by analyzing the numerical values ​​of all real-time communication base station operation data to determine whether they are in the communication base station normal state operation data range interval corresponding to the communication base station operation data category;

[0157] The abnormal operation status category matching module matches the real-time communication base station operation data set with each abnormal operation status category in the abnormal operation status category set one by one through a black hole algorithm;

[0158] The solution optimization module searches for the optimal solution for the matching result in the communication base station operation status management unit through the krill swarm optimization algorithm;

[0159] The abnormal operation status processing module operation and maintenance personnel issue corresponding operation instructions to the communication base station abnormal operation status processing unit according to the optimal solution, adjust the equipment in the communication base station, and perform the corresponding next step according to whether the alarm is lifted.

[0160] In the description of this specification, the descriptions referring to the terms "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the 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.

[0161] The preferred embodiments of the invention disclosed above are only used to help illustrate the invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification in order to better explain the principles and practical applications of the invention, so that those skilled in the art can well understand and utilize the invention.

Claims

1. A method for supervising data interaction of a communication base station based on data interaction, characterized in that: The steps include: S1. Collect abnormal operation status data in historical data, cluster the abnormal operation status data using an agglomerative hierarchical clustering algorithm, and establish an abnormal operation status category set based on various abnormal operation status data clusters obtained after clustering; S2. Setting a communication base station operation data category set, collecting communication base station operation data of each communication base station operation data category in the communication base station operation data category set in real time, and obtaining a real-time communication base station operation data set; S3, feeding back the real-time communication base station operation data set to the communication base station operation status monitoring unit to determine the real-time operation status of the communication base station; S4. When the real-time operation status of the communication base station is determined to be an abnormal operation status, the real-time communication base station operation data set is matched with each abnormal operation status category in the abnormal operation status category set one by one, and the matching result is fed back to the communication base station operation status management unit and an alarm is issued. S4 includes the following steps: S41, when the real-time operation state of the communication base station is determined to be an abnormal operation state, matching the real-time communication base station operation data set with each abnormal operation state category in the abnormal operation state category set one by one; S411. Build planet population and set maximum number of iterations t max and population size l; Each abnormal operation state category in the abnormal operation state category set is regarded as a planetary individual, and an initial position set of l planetary individuals is randomly generated in the search space; S412, calculating the fitness function value of each planetary individual in the planetary population, comparing the fitness function values ​​of all planetary individuals, and selecting the planetary individual with the largest fitness function value as the black hole; S413. When the position of the black hole is determined, all non-black hole planets will be affected by the gravitational force of the black hole and move toward the black hole along a certain trajectory; S414, calculating the fitness function value of the new position reached by each planet individual after the position update, if the fitness function value of the new position is higher than the fitness function value of the black hole position, then the planet individual replaces the previous black hole to become the new black hole, and the previous black hole becomes a planet again and moves towards the new black hole; S415. Under the gravitational force of the black hole, the planet will continue to approach the black hole. When the distance between a planet and the black hole is less than the distance threshold, the planet will be absorbed by the black hole, and a new planet individual will be randomly generated in the search space. S416: Determine whether the maximum number of iterations t has been reached max , if not, return to S413; if reached, take the black hole as the current global optimal solution, set the fitness function threshold, when the fitness function value of the black hole is greater than the fitness function threshold, the abnormal operation state category corresponding to the current global optimal solution successfully matches the real-time communication base station operation data set; otherwise, the real-time communication base station operation data and each abnormal operation state category in the abnormal operation state category set fail to match; S42, if the match is successful, the abnormal operation status category that successfully matches the real-time communication base station operation data set is fed back to the communication base station operation status management unit and an alarm is issued; If the real-time communication base station operation data set fails to match each abnormal operation status category in the abnormal operation status category set, a new abnormal operation status category is set for the real-time communication base station operation data set and stored in the abnormal operation status category set, and the abnormal operation status category is fed back to the communication base station operation status management unit and an alarm is issued; S5, the communication base station operation status management unit searches for an optimal solution according to the matching result, and S5 includes the following steps: S51, construct the krill population, set the current number of iterations and the maximum number of iterations to T max , population size N, maximum induced movement speed, induced weight, maximum foraging movement speed, foraging weight, maximum random diffusion movement speed, movement period of krill individuals and initial position set of krill population; S52, calculating the fitness function value of each krill individual in the krill population, and taking the krill individual with the highest fitness as the current optimal krill individual; S53. Calculate the movement speed of krill individuals according to the effects of induction, foraging and random diffusion on krill individuals; S531. Krill individuals in a krill population will be induced to move by nearby krill individuals and the best krill individuals. S532. Krill individuals in a krill population forage based on food location and previous foraging experience; S533. Krill individuals in a krill population will diffuse randomly according to the maximum diffusion speed and the randomly selected movement direction; S54, updating the position of the krill individual according to the movement speed of each krill individual in the krill population; S55, for each krill individual in the krill population, randomly select other krill individuals according to the set crossover probability to perform a crossover operation to generate new krill individuals; S56, performing a mutation operation on each krill individual in the krill population according to a set mutation probability to generate a new krill individual; S57, calculating the fitness function values ​​of all krill individuals after position update and new krill individuals generated after crossover and mutation operations, arranging them from large to small according to the fitness function values, and selecting N krill individuals with the highest fitness function values ​​as the new krill population; S58, determine whether the maximum number of iterations T is reached max If it is not reached, return to S53; if it is reached, take the krill individual with the highest fitness function value as the global optimal solution, and output the solution corresponding to the global optimal solution as the optimal solution; S6. The communication base station abnormal operation status processing unit issues corresponding operation instructions according to the optimal solution.

2. A method for supervising data interaction of communication base stations based on data interaction according to claim 1, characterized in that: The S1 comprises the following steps: S11, collecting abnormal operation status data in historical data, treating each abnormal operation status data as a cluster, calculating the Euclidean distance between clusters, and obtaining a distance matrix; S12, finding two clusters with the shortest Euclidean distance from the distance matrix, merging them into a new cluster, and calculating the Euclidean distance between the new cluster and the other clusters; S13, repeat S11 and S12 until the Euclidean distance between each cluster obtained after clustering is greater than the set Euclidean distance threshold, then stop clustering, and establish an abnormal operation status category set according to the various abnormal operation status data clusters obtained after clustering.

3. A method for supervising data interaction of communication base stations based on data interaction according to claim 2, characterized in that: The S2 comprises the following steps: S21, set the communication base station operation data category set B = (b1, b2, ..., b i ,…,b l ), where b i represents the i-th communication base station operation data category, l represents the total number of communication base station operation data categories; S22, collect the communication base station operation data category set B in real time through the data collection device = (b1, b2, ..., b i ,…,b l ) to obtain the communication base station operation data set in real time.

4. A method for supervising data interaction of communication base stations based on data interaction according to claim 3, characterized in that: The S3 comprises the following steps: S31. Setting the communication base station normal state operation data range interval set in, and They respectively represent the minimum and maximum values ​​of the normal state operation data of the i-th communication base station operation data category; S32. After receiving the feedback of the real-time communication base station operation data set, the communication base station operation status monitoring unit determines in turn whether the numerical value of each real-time communication base station operation data in the real-time communication base station operation data set is within the corresponding communication base station normal state operation data range interval in the communication base station normal state operation data range interval set; if the numerical values ​​of all the real-time communication base station operation data are within the corresponding communication base station normal state operation data range interval, then the real-time operation status of the communication base station is determined to be a normal operation status; otherwise, then the real-time operation status of the communication base station is determined to be an abnormal operation status.

5. A method for supervising data interaction of communication base stations based on data interaction according to claim 4, characterized in that: The S6 comprises the following steps: S61, the communication base station operation state management unit sends corresponding operation instructions to the communication base station abnormal operation state processing unit according to the output optimal solution, and regulates the equipment in the communication base station; S611, if the alarm is relieved after the equipment is regulated, the operation is terminated; If the alarm is not lifted after equipment adjustment, further adjustment and maintenance will be carried out on site based on the real-time communication base station operation data and the corresponding abnormal operation status category.

6. A system for implementing the communication base station data interaction supervision method based on data interaction as described in any one of claims 1-5, comprising an abnormal operation status category set construction module, a real-time communication base station operation data acquisition module, a communication base station real-time operation status determination module, an abnormal operation status category matching module, a solution optimization module, and an abnormal operation status processing module.

Images