An alarm control system based on self-learning algorithm and concurrent data communication

Abstract

The present invention discloses an alarm control system based on a self-learning algorithm and concurrent data communication, comprising an alarm control center and a plurality of alarm controllers; the alarm control center comprises a central business processing module, a transceiver module A, a transceiver module B, a communication measurement module A, a communication measurement module B, an optimization calculation module, a communication parameter control and distribution module, and a measurement data and optimization parameter storage module; the transceiver module A and the transceiver module B respectively send data to the communication measurement module A and the communication measurement module B for calculation and storage according to the requirements of the central business processing module, and then send the data to the optimization calculation module; the optimization calculation module calculates the communication parameters from the data and sends them to the transceiver module A, the transceiver module B or the communication parameter control and distribution module for execution; the alarm controller is communicatively connected to the alarm control center, and the terminal communication time point and channel access strategy are determined by the alarm controller.

Description

Technical Field

[0001] The present invention relates to the technical field of alarm control systems, and in particular to an alarm control system based on a self-learning algorithm and concurrent data communication. Background Art

[0002] The alarm control system consists of an alarm control center and an alarm controller. After the alarm control center issues an alarm control command or status query command, the alarm controller must send alarm response information or its own operating status information back to the alarm control center. Limited by the narrowband and low-bandwidth characteristics of the alarm wireless communication network, coordination and control of wireless communications between the alarm control center and the alarm controller are necessary to improve data transmission throughput. Common coordination mechanisms include: 1) The alarm control center polls the alarm controllers, which transmit data in the polling order. The alarm control center can confirm or deny successful communication, and if unsuccessful, it can arrange for another operation. This method can effectively reduce wireless channel conflicts, but requires at least two rounds of two-way wireless communication. Failures in communication may also lead to more wireless communications due to retrying transmissions. 2) The alarm control center initiates batch query commands. The alarm controllers are arranged in order according to an agreed-upon algorithm and initiate communication at a predetermined time point in a predetermined order and time interval. The alarm control center can confirm or deny successful transmission. 3) The alarm control center initiates a batch query command. The alarm controller calculates the random backoff time interval according to the agreed algorithm and initiates competitive communication. The successful contestant obtains communication authorization to transmit data, or directly transmits data during the competition. After receiving successful confirmation, the transmission is completed. If no successful confirmation information is received, the competitive transmission continues.

[0003] In the alarm control system, under different wireless network communication technology systems and different numbers of alarm controllers, the sorting and random competition algorithms used by different coordination mechanisms will produce different effects. In the construction of the existing civil air defense multi-means alarm system, a wireless communication network based on the civil air defense wireless private network (such as Figure 1 As shown) and based on MDT digital trunking communication network (as Figure 2 There are two wireless communication networks (as shown in FIG), and there are significant differences in the mechanisms and performances of these two wireless communication networks, which brings greater difficulties to the transmission coordination mechanism of the alarm control feedback data and the terminal working status data. Summary of the Invention

[0004] The purpose of the present invention is to provide an alarm control system based on self-learning algorithm and concurrent data communication. The alarm control system based on self-learning algorithm and concurrent data communication initially adopts default strategies and parameters, and through multiple communications, gradually adjusts the communication strategies, algorithms and parameters to achieve dynamic regulation of the communication mechanism.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] An alarm control system based on a self-learning algorithm and concurrent data communication comprises an alarm control center and several alarm controllers; the alarm control center comprises a central business processing module, a transceiver module A, a transceiver module B, a communication measurement module A, a communication measurement module B, an optimization calculation module, a communication parameter control and distribution module, and a measurement data and optimization parameter storage module; the transceiver module A and the transceiver module B respectively send data to the communication measurement module A and the communication measurement module B for calculation and storage according to the requirements of the central business processing module, and then send the data to the optimization calculation module; the optimization calculation module uses a communication control parameter optimization algorithm to calculate the communication parameters from the data and then sends them to the transceiver module A, the transceiver module B or the communication parameter control and distribution module for execution; the alarm controller is communicatively connected to the alarm control center, and the alarm controller determines the terminal communication time point and channel access strategy to realize dynamic regulation of the communication mechanism.

[0007] Preferably, the alarm controller includes a terminal service processing module, a transceiver module C, a transceiver module D, a sorting control random backoff algorithm module and a communication parameter storage module; the terminal service module is connected to the alarm control center through the transceiver module C or the transceiver module D, and after the terminal service module receives the communication parameter update instruction for the local device issued by the alarm control center, the terminal service module sends the instruction and data to the sorting control random backoff algorithm module, and the sorting control random backoff algorithm module updates the communication parameter storage module; the sorting control random backoff algorithm module obtains the calculation parameters by accessing the communication parameter storage module; when the transceiver module C or the transceiver module D communicates with the alarm control center, the terminal communication time point and channel access strategy are determined by calling the sorting control random backoff algorithm module.

[0008] Preferably, the alarm controller has a default multiple sorting control random backoff algorithm module and communication parameters, initially adopts the default strategy and parameters, and gradually adjusts the communication strategy, algorithm and parameters through multiple communications to achieve dynamic regulation of the communication mechanism.

[0009] Preferably, the optimization calculation module is used to convert and process the provided data and store it in the measurement data and optimization parameter storage module, and based on historical and current data, integrate all alarm terminal communication test data and network networking information to perform calculations based on the model to calculate the communication parameters that conform to the overall network and each alarm terminal; wherein, the communication parameters suitable for a single alarm controller are sent to the corresponding alarm controller through the transceiver module A and the transceiver module B by calling the communication parameter control and sending module; the communication parameters that conform to the overall network communication coordination are sent to the transceiver module A or the transceiver module B, and the data sending and receiving strategy is updated and executed.

[0010] Preferably, the processing of the communication measurement module A and the communication measurement module B includes the following steps:

[0011] S1. Combined with the communication frame structure, the communication base station and the intermediate station / relay station collaborate to measure the communication indicators and calculate and store the following data: for the i-th two-way communication, the control center sends the command time stamp number and the response data reception time stamp to calculate the communication delay time as Tij; where i is the communication number and j is the communication site number; the base station and intermediate station / relay station number currently connected to site j is recorded as Bij; the signal strength level of the key site received by the base station and intermediate station / relay station is recorded as Sij; the number of retransmissions or failures of the alarm terminal data transmission is recorded as Fij; the communication parameters of a single communication are stored in the set: Ri = {i, j, Tij, Bij, Sij, Fij}; for communications that fail to return data, Tij is set to the special value FFFF, and Sij and Fij are set to null values;

[0012] S2. Based on the basic site information, store the latitude and longitude coordinates Pj of the network central controller, base station, intermediate station / relay station, and terminal, and calculate the numbers and distance levels of the three base stations closest to site j, which are recorded as: Ci1, Ci2, Ci3, Di1, Di2, Di3; where Cix is ​​the base station number and Dix is ​​the distance level; the site network set is recorded as: Ni = {I, Ci1, Ci2, Ci3, Di1, Di2, Di3}; distance level Dix = 10logD + a; where D is the actual physical distance in km; a is an empirical constant ranging from 1.0 to 5.

[0013] S3. Output communication parameters include communication parameters sent to each alarm site. The parameter value set for site i is: Ki = {i, Bi, Li, Mi, Oi, Pi}; where Bi is the base station, intermediate station / relay station number to which site i should connect; Li is the average waiting interval time, in ms; Mi is the offset, in ms; Oi is the random backoff algorithm index number, which includes three different calculation methods built into the terminal; and Pi is the seed of the random algorithm.

[0014] Preferably, the communication control parameter optimization algorithm in the optimization calculation module is: based on the Ni = {I, Ci1, Ci2, Ci3, Di1, Di2, Di3} set and the Ri = {i, j, Tij, Bij, Sij, Fij} set, the optimal Ki = {i, Bi, Li, Mi, Oi, Pi} set is dynamically calculated; wherein the Ni set is static data, and the Ri set gradually increases with the increase in the number of communications; Ki is calculated based on the results of the autonomous learning algorithm, and new data is added when the site communication parameters need to be adjusted; the utility evaluation target of the optimization effect is the overall network communication success rate and the optimal total duration, and the utility function is the minimum accumulated value of Tij in the most recent Ri set; the initial Ki set is generated by learning a 6-layer convolutional neural network algorithm through manual supervision based on the network structure and the simulated experimental environment; the trained algorithm is used for the dynamic parameter optimization process, and during the dynamic operation process, the Ni set and the Ri set are regularly sent to the optimization calculation module in the form of data files, and the optimization calculation module then sends the calculated values ​​to the communication parameter sending module in the form of data files.

[0015] Preferably, the random backoff algorithm in the sorting control random backoff algorithm module is: a Rand() function calculation method with a minimum and maximum value limit, P is the random algorithm seed issued, the result values ​​produced by the same seed have statistical differences, and the generated results are randomly and evenly distributed in the valid numerical segment.

[0016] Preferably, the random backoff algorithm in the sorting control random backoff algorithm module is: a Rand() function calculation method with a minimum and maximum value limit, P is the random algorithm seed issued, the result values ​​produced by the same seed have statistical differences, and the generated results are normally distributed in the valid numerical range.

[0017] Preferably, the random backoff algorithm in the sorting control random backoff algorithm module is a Rand() function calculation method with a minimum and maximum value limited, and the backoff value range increases with an exponential function and decreases at equal intervals.

[0018] After adopting the above technical solution, the present invention has the following advantages compared with the background technology: the present invention provides an alarm control system based on concurrent data communication of a self-learning algorithm, which is optimized for the concurrent data communication scenario of the alarm terminal of the alarm control system. The optimization calculation adopts a self-learning algorithm, which can be dynamically optimized according to the network scale and actual performance. Its communication strategy, algorithm, and parameters can be dynamically adjusted, and separate parameters are calculated for each alarm controller. It supports one communication system or two communication systems at the same time. The communication strategies, algorithms, and parameters of the two communication systems are independently calculated and stored, which greatly simplifies the optimization work of the alarm communication network, improves the network communication optimization efficiency, reduces wireless communication conflicts and interference, improves the communication success rate of the system, and reduces the overall concurrent communication time, thereby realizing dynamic regulation of the communication mechanism. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a schematic diagram of the existing wireless communication network based on the civil air defense wireless private network;

[0020] Figure 2 This is a schematic diagram of the existing MDT-based digital trunking communication network;

[0021] Figure 3 Schematic diagram of the alarm control center and alarm controller of the present invention.

[0022] The reference numerals in the figures are as follows:

[0023] 1. Alarm control center; 10. Central business processing module; 11. Transceiver module A; 12. Transceiver module B; 13. Communication measurement module A; 14. Communication measurement module B; 15. Optimization calculation module; 16. Communication parameter control and distribution module; 17. Measurement data and optimization parameter storage module; 2. Alarm controller; 20. Terminal business processing module; 21. Transceiver module C; 22. Transceiver module D; 23. Sorting control random backoff algorithm module; 24. Communication parameter storage module. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0025] It should be noted that in the present invention, the terms "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc. are all based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element of the present invention must have a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0026] Example

[0027] like Figures 1 to 3As shown, the present invention discloses an alarm control system based on self-learning algorithm and concurrent data communication, comprising an alarm control center 1 and several alarm controllers 2; the alarm control center 1 comprises a central business processing module 10, a transceiver module A11, a transceiver module B12, a communication measurement module A13, a communication measurement module B14, an optimization calculation module 15, a communication parameter control and distribution module 16 and a measurement data and optimization parameter storage module 17; the transceiver module A11 and the transceiver module B12 send data to the communication measurement module A13 and the communication measurement module B14 according to the requirements of the central business processing module 10 respectively. After B14 performs calculation and storage, the data is sent to the optimization calculation module 15. The transceiver module A11 and the transceiver module B12 correspond to the wireless communication network based on the civil defense wireless private network and the MDT digital cluster communication network respectively; the optimization calculation module 15 uses the communication control parameter optimization algorithm to calculate the communication parameters from the data and then sends them to the transceiver module A11, the transceiver module B12 or the communication parameter control and sending module 16 for execution; the alarm controller 2 is communicated with the alarm control center 1, and the terminal communication time point and channel access strategy are determined by the alarm controller 2 to realize dynamic regulation of the communication mechanism.

[0028] like Figure 3 As shown, the alarm controller 2 includes a terminal business processing module 20, a transceiver module C21, a transceiver module D22, a sorting control random backoff algorithm module 23 and a communication parameter storage module 24; the terminal business module is connected to the alarm control center 1 through the transceiver module C21 or the transceiver module D22. After receiving the communication parameter update instruction for the local device issued by the alarm control center 1, the terminal business module sends the instruction and data to the sorting control random backoff algorithm module 23, and the sorting control random backoff algorithm module 23 updates the communication parameter storage module 24; the sorting control random backoff algorithm module 23 obtains the calculation parameters by accessing the communication parameter storage module 24; when the transceiver module C21 or the transceiver module D22 communicates with the alarm control center 1, the terminal communication time point and channel access strategy are determined by calling the sorting control random backoff algorithm module 23. The transceiver module C21 and the transceiver module D22 correspond to the wireless communication network based on the civil air defense wireless private network and the MDT digital cluster communication network, respectively.

[0029] like Figure 3 As shown, the alarm controller 2 has a default multiple sorting control random backoff algorithm module 23 and communication parameters. Initially, the default strategy and parameters are adopted. Through multiple communications, the communication strategy, algorithm and parameters are gradually adjusted to achieve dynamic regulation of the communication mechanism.

[0030] like Figure 3As shown, the optimization calculation module 15 is used to convert and process the provided data and store it in the measurement data and optimization parameter storage module 17, and based on historical and current data, integrate all alarm terminal communication test data and network networking information to perform calculations based on the model to calculate the communication parameters that meet the overall network and each alarm terminal; among them, the communication parameters suitable for a single alarm controller 2 are sent to the corresponding alarm controller 2 through the transceiver module A11 and the transceiver module B12 by calling the communication parameter control and sending module 16; the communication parameters that meet the overall network communication coordination are sent to the transceiver module A11 or the transceiver module B12, and the data sending and receiving strategy is updated and executed.

[0031] like Figure 3 As shown, the processing of the communication measurement module A13 and the communication measurement module B14 includes the following steps:

[0032] S1. Combined with the communication frame structure, the communication base station and the intermediate station / relay station collaborate to measure the communication indicators and calculate and store the following data: for the i-th two-way communication, the control center sends the command time stamp number and the response data reception time stamp to calculate the communication delay time as Tij; where i is the communication number and j is the communication site number; the base station and intermediate station / relay station number currently connected to site j is recorded as Bij; the signal strength level of the key site received by the base station and intermediate station / relay station is recorded as Sij; the number of retransmissions or failures of the alarm terminal data transmission is recorded as Fij; the communication parameters of a single communication are stored in the set: Ri = {i, j, Tij, Bij, Sij, Fij}; for communications that fail to return data, Tij is set to the special value FFFF, and Sij and Fij are set to null values;

[0033] S2. Based on the basic site information, store the latitude and longitude coordinates Pj of the network central controller, base station, intermediate station / relay station, and terminal, and calculate the numbers and distance levels of the three base stations closest to site j, which are recorded as: Ci1, Ci2, Ci3, Di1, Di2, Di3; where Cix is ​​the base station number and Dix is ​​the distance level; the site network set is recorded as: Ni = {I, Ci1, Ci2, Ci3, Di1, Di2, Di3}; distance level Dix = 10logD + a; where D is the actual physical distance in km; a is an empirical constant ranging from 1.0 to 5.

[0034] S3. Output communication parameters include communication parameters sent to each alarm site. The parameter value set for site i is: Ki = {i, Bi, Li, Mi, Oi, Pi}; where Bi is the base station, intermediate station / relay station number to which site i should connect; Li is the average waiting interval time, in ms; Mi is the offset, in ms; Oi is the random backoff algorithm index number, which includes three different calculation methods built into the terminal; and Pi is the seed of the random algorithm.

[0035] like Figure 3 As shown, the communication control parameter optimization algorithm in the optimization calculation module 15 is as follows: based on the set Ni = {I, Ci1, Ci2, Ci3, Di1, Di2, Di3} and the set Ri = {i, j, Tij, Bij, Sij, Fij}, the optimal set Ki = {i, Bi, Li, Mi, Oi, Pi} is dynamically calculated; wherein the Ni set is static data, and the Ri set gradually increases with the increase in the number of communications; Ki is calculated based on the results of the autonomous learning algorithm, and new data is added when the site communication parameters need to be adjusted; the utility evaluation target of the optimization effect is the overall network communication success rate and the optimal total duration, and the utility function is the minimum accumulated value of Tij in the most recent Ri set; the initial Ki set is generated by learning a 6-layer convolutional neural network algorithm through manual supervision based on the network structure and the simulated experimental environment; the trained algorithm is used for the dynamic parameter optimization process. During the dynamic operation process, the Ni set and the Ri set are regularly sent to the optimization calculation module 15 in the form of data files, and the optimization calculation module 15 then sends the calculated values ​​to the communication parameter distribution module in the form of data files.

[0036] like Figure 3 As shown, the random backoff algorithm in the sorting control random backoff algorithm module 23 is: the Rand() function calculation method with limited minimum and maximum values, P is the random algorithm seed issued, the result values ​​produced by the same seed have statistical differences, and the generated results are randomly and evenly distributed in the valid numerical range.

[0037] like Figure 3 As shown, the random backoff algorithm in the sorting control random backoff algorithm module 23 is: the Rand() function calculation method with limited minimum and maximum values, P is the random algorithm seed issued, the result values ​​produced by the same seed have statistical differences, and the generated results are normally distributed in the valid numerical range.

[0038] like Figure 3 As shown, the random backoff algorithm in the sorting control random backoff algorithm module 23 is a Rand() function calculation method with a minimum and maximum value limited, and the backoff value range increases with an exponential function and decreases at equal intervals.

[0039] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. An alarm control system based on a self-learning algorithm and concurrent data communication, characterized by: It includes an alarm control center and several alarm controllers; the alarm control center includes a central business processing module, a transceiver module A, a transceiver module B, a communication measurement module A, a communication measurement module B, an optimization calculation module, a communication parameter control and distribution module, and a measurement data and optimization parameter storage module; the transceiver module A and the transceiver module B send data to the communication measurement module A and the communication measurement module B respectively according to the needs of the central business processing module for calculation and storage, and then send the data to the optimization calculation module; the optimization calculation module uses a communication control parameter optimization algorithm to calculate the communication parameters from the data and then sends them to the transceiver module A, the transceiver module B or the communication parameter control and distribution module for execution; the alarm controller is connected to the alarm control center for communication, and the alarm controller determines the terminal communication time point and channel access strategy to realize dynamic regulation of the communication mechanism; The alarm controller includes a terminal service processing module, a transceiver module C, a transceiver module D, a sorting control random backoff algorithm module, and a communication parameter storage module; the terminal service processing module is connected to the alarm control center through the transceiver module C or the transceiver module D. After receiving the communication parameter update instruction for the terminal from the alarm control center, the terminal service processing module sends the instruction and data to the sorting control random backoff algorithm module, and the sorting control random backoff algorithm module updates the communication parameter storage module; the sorting control random backoff algorithm module obtains calculation parameters by accessing the communication parameter storage module; when the transceiver module C or the transceiver module D communicates with the alarm control center, it determines the terminal communication time point and channel access strategy by calling the sorting control random backoff algorithm module; The alarm controller has a default multiple sorting control random backoff algorithm module and communication parameters. It initially adopts the default strategy and parameters, and gradually adjusts the communication strategy, algorithm and parameters through multiple communications to achieve dynamic regulation of the communication mechanism.

2. The alarm control system based on self-learning algorithm and concurrent data communication according to claim 1, characterized in that: The optimization calculation module is used to convert and process the provided data and store it in the measurement data and optimization parameter storage module, and based on historical and current data, integrate all alarm terminal communication test data and network networking information to perform calculations based on the model to calculate the communication parameters that conform to the overall network and each alarm terminal; among them, the communication parameters suitable for a single alarm controller are sent to the corresponding alarm controller through the transceiver module A and the transceiver module B by calling the communication parameter control and sending module; the communication parameters that conform to the overall network communication coordination are sent to the transceiver module A or the transceiver module B, and the data sending and receiving strategy is updated and executed.

3. The alarm control system based on self-learning algorithm and concurrent data communication according to claim 1, characterized in that: The processing process of the communication measurement module A and the communication measurement module B includes the following steps: S1. Combined with the communication frame structure, the communication base station and the intermediate station / relay station collaborate to measure the communication indicators and calculate and store the following data: for the i-th two-way communication, the control center sends the command time stamp number and the response data reception time stamp to calculate the communication delay time as Tij; where i is the communication number and j is the communication site number; the base station and intermediate station / relay station number currently connected to site j is recorded as Bij; the signal strength level of the key site received by the base station and intermediate station / relay station is recorded as Sij; the number of retransmissions or failures of the alarm terminal data transmission is recorded as Fij; the communication parameters of a single communication are stored in the set: Ri = {i, j, Tij, Bij, Sij, Fij}; for communications that fail to return data, Tij is set to the special value FFFF, and Sij and Fij are set to null values; S2. Based on the basic site information, store the latitude and longitude coordinates Pj of the network central controller, base station, intermediate station / relay station, and terminal, and calculate the numbers and distance levels of the three base stations closest to site j, which are recorded as: Ci1, Ci2, Ci3, Di1, Di2, Di3; where Cix is ​​the base station number and Dix is ​​the distance level; the site network set is recorded as: Ni = {I, Ci1, Ci2, Ci3, Di1, Di2, Di3}; distance level Dix = 10logD + a; where D is the actual physical distance in km; a is an empirical constant ranging from 1.0 to 5. S3. Output communication parameters include communication parameters sent to each alarm site. The parameter value set for site j is: Ki = {i, Bi, Li, Mi, Oi, Pi}; where Bi is the base station, intermediate station / relay station number to which site j should connect; Li is the average waiting interval time, in ms; Mi is the offset, in ms; Oi is the random backoff algorithm index number, which includes three different calculation methods built into the terminal; and Pi is the seed of the random algorithm.

4. The alarm control system based on self-learning algorithm and concurrent data communication as claimed in claim 3, characterized in that: The communication control parameter optimization algorithm in the optimization calculation module is as follows: based on the set Ni = {I, Ci1, Ci2, Ci3, Di1, Di2, Di3} and the set Ri = {i, j, Tij, Bij, Sij, Fij}, the optimal set Ki = {i, Bi, Li, Mi, Oi, Pi} is dynamically calculated; wherein the Ni set is static data and the Ri set gradually increases with the increase in the number of communications; Ki is calculated based on the results of the autonomous learning algorithm, and new data is added when the site communication parameters need to be adjusted; the utility evaluation target of the optimization effect is the overall network communication success rate and the optimal total duration, and the utility function is the minimum accumulated value of Tij in the most recent Ri set; the initial Ki set is generated by learning a 6-layer convolutional neural network algorithm through manual supervision based on the network structure and simulated experimental environment; the trained algorithm is used for the dynamic parameter optimization process. During the dynamic operation process, the Ni set and the Ri set are regularly sent to the optimization calculation module in the form of data files, and the optimization calculation module then sends the calculated values ​​to the communication parameter distribution module in the form of data files.

5. The alarm control system based on self-learning algorithm and concurrent data communication according to claim 1, characterized in that: The random backoff algorithm in the sorting control random backoff algorithm module is: the Rand() function calculation method with limited minimum and maximum values, P is the random algorithm seed issued, the result values ​​produced by the same seed have statistical differences, and the generated results are randomly and evenly distributed in the valid numerical range.

6. The alarm control system based on self-learning algorithm and concurrent data communication according to claim 1, characterized in that: The random backoff algorithm in the sorting control random backoff algorithm module is: a Rand() function calculation method with a minimum and maximum value limit, P is the random algorithm seed issued, the result values ​​produced by the same seed have statistical differences, and the generated results are normally distributed in the valid numerical range.

7. The alarm control system based on self-learning algorithm and concurrent data communication according to claim 1, characterized in that: The random backoff algorithm in the sorting control random backoff algorithm module is a Rand() function calculation method with a minimum and maximum value limited, and the backoff value range increases with an exponential function and decreases at equal intervals.

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