A transmission control method based on data network

Abstract

The present invention discloses a data network-based transmission control method, which specifically relates to the field of communication control technology, comprising: collecting fault data of data transmission nodes in abnormal geographical areas, the fault data including the time and location of each fault occurrence; analyzing the fault data in each geographical area, calculating the ratio of the number of fault nodes to the total number of nodes at each time point, and obtaining a fault time distribution coefficient; calculating the ratio of the number of fault nodes at each location to the total number of nodes, and obtaining a fault space distribution coefficient; jointly analyzing the fault time distribution coefficient and the fault space distribution coefficient to obtain a transmission performance balance index of the data transmission nodes in each area; guiding the resource allocation priority of the geographical area based on the transmission performance balance index, and outputting the abnormal area of the data network, thereby solving the problem in the prior art that resource allocation is often based on experience or fixed rules, making it difficult to achieve optimal resource configuration and efficient utilization.

Description

Technical Field

[0001] The present invention relates to the field of communication control technology, and more particularly to a data network-based transmission control method. Background Art

[0002] In the current field of communication control technology, data network transmission control methods face unprecedented challenges, primarily due to the rapid expansion and increasing complexity of networks. Data transmission inevitably encounters various factors, such as network congestion, equipment failures, and natural disasters. These factors can cause data loss, delays, or interruptions, severely impacting service continuity and user experience. To address these challenges, transmission control methods have emerged. Their core goal is to ensure stable and reliable data transmission by monitoring network status in real time, accurately predicting and effectively addressing potential issues.

[0003] However, in actual use, it still has many shortcomings, such as lack of real-time performance: traditional methods usually rely on regular data collection and analysis, resulting in slow response to network failures and inability to take effective control measures in a timely manner; unreasonable resource allocation: due to the lack of scientific performance evaluation methods, resource allocation is often based on experience or fixed rules, making it difficult to achieve optimal resource configuration and efficient utilization. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a transmission control method based on a data network, which divides the data network into several geographical areas, and screens and obtains the number of the geographical area with abnormal data transmission according to the communication quality of the geographical area; collects the fault data of the data transmission nodes with the number of the geographical area with abnormal data transmission, and the fault data includes the time and location of each fault; analyzes the fault data to obtain the fault time distribution coefficient and the fault space distribution coefficient; jointly analyzes the fault time distribution coefficient and the fault space distribution coefficient to obtain the transmission performance balance index of the geographical area with abnormal data transmission; and guides the geographical area to take measures based on the transmission performance balance index to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a data network-based transmission control method, comprising the following steps:

[0006] Step 1: Receive the ID of the data transmission abnormal geographical area, and collect the fault data of the data transmission nodes in each data transmission abnormal geographical area, wherein the fault data includes the time and location of each fault occurrence;

[0007] Step 2: Analyze the fault data and calculate the ratio of the number of faulty nodes to the total number of nodes at each time point to obtain the fault time distribution coefficient FT and the fault space distribution coefficient FK;

[0008] Step 3: Jointly analyze the fault time distribution coefficient and the fault space distribution coefficient, and use the formula Calculate the transmission performance balance index CJ of each regional data transmission node;

[0009] Step 4: Take regulatory measures based on the transmission performance balance index; compare the calculated transmission performance balance index with the preset threshold. When the transmission performance balance index is lower than the threshold, the geographical area with abnormal data transmission will increase resource investment, optimize the network structure, and adjust the load balancing strategy.

[0010] Preferably, the failure time distribution coefficient is obtained as follows:

[0011] Divide the communication network operation information into several time windows and obtain the number of faulty nodes in each time window. Suppose there are m time windows and j represents the sequence number of the time windows.

[0012] Let k represent the sequential number of the time points in the time window, and obtain the number of faulty nodes detected at the kth time point; N represents the total number of data transmission nodes, k traverses the time points from time t-w+1 to time t; w represents the number of time points in the time window;

[0013] By formula Calculate the average failure rate Ftd in the jth time window j ; Where Fk represents the number of faulty nodes detected at the kth time point;

[0014] By formula The failure time distribution coefficient is calculated.

[0015] Preferably, the fault spatial distribution coefficient is obtained as follows:

[0016] The communication network operation information is divided into several locations according to the data transmission nodes, and the cumulative number of failures F at each location is obtained. P ; Use p to represent the position number of the data transmission node, Q to represent the total number of data transmission nodes; through the formula Calculate the failure rate of the pth position; by formula The fault spatial distribution coefficient is calculated.

[0017] Preferably, if the transmission performance balance index is lower than the threshold, it means that the performance of the data transmission abnormal geographical area corresponding to the transmission performance balance index has declined significantly, and immediate measures need to be taken to intervene; if the transmission performance balance index exceeds the threshold, it means that the performance of the data transmission abnormal geographical area is still within an acceptable range, but its changing trend needs to be continuously monitored.

[0018] Preferably, the transmission control method includes a data visualization interaction module, which is used to transmit the fault transmission node distribution map and the transmission performance balance index to the user end. The fault transmission node distribution map is obtained by: drawing a fault transmission node position distribution map that changes with time; using the collected fault data, the horizontal axis represents time and the vertical axis represents the position of the transmission node to draw a fault time-space two-dimensional map. On the fault time-space two-dimensional map, each fault point is represented by a mark, thereby obtaining a fault transmission node distribution map that changes with time.

[0019] Preferably, the transmission control method comprises the following steps:

[0020] Step 5: Use the failure rate data of each time window and each data transmission node in the historical time period as the input of the failure rate prediction model, and output the predicted failure rate in the future time window and at each data transmission node location;

[0021] Step 6: Screen potential faulty data nodes based on the predicted fault occurrence rate of each data transmission node location; and prompt the user to maintain the potential faulty data nodes.

[0022] Preferably, the process of acquiring the failure occurrence rate prediction model includes the following steps:

[0023] Step S11, data preparation: collect and organize time series data, including the failure rate of each time window and each location;

[0024] Step S12: Check the data to see if it is stable. If it is not stable, differential transformation is required.

[0025] Step S13, model identification: using the autocorrelation function and the partial autocorrelation function to determine the parameter factors of the ARIMA model;

[0026] Step S14, model fitting: fitting the ARIMA model based on the obtained parameter factors;

[0027] Step S15, model diagnosis: check whether the residuals of the model are random and independent to ensure the validity of the model and obtain a well-fitted fault occurrence rate prediction model;

[0028] Step S16, prediction: using the fitted fault incidence prediction model to predict the fault incidence in the next time window and at each location;

[0029] Step S17, verification and feedback: Use actual data to verify the accuracy of the prediction and adjust the failure rate prediction model as needed.

[0030] Preferably, the method for obtaining the data transmission abnormal geographical area number is:

[0031] Collect monitoring log information of data transmission nodes in each geographical area, where i represents the number of geographical areas and n represents the number of geographical areas;

[0032] Obtain the average upload speed and download speed of the i-th geographical area, which are recorded as Us and Ds respectively; obtain the upload failure rate and download failure rate of the i-th geographical area, which are recorded as Uf and Df respectively;

[0033] By formula The basic speed quality Btv_i of the i-th geographical area is calculated, where γ represents the weight factor for adjusting the impact of the failure rate;

[0034] By formula The load reduction factor LP_i of the i-th geographical area is calculated, where λ represents the parameter that controls the shape of the reduction curve; Fth represents the load threshold, exceeding which the communication transmission speed is considered to be affected; LF represents the sum of the upload load and the download load;

[0035] Obtain the communication speed quality index TV_i of the i-th geographical area; calculate the communication speed quality index Tz_i by the formula Tz_i=Btv_i*LP_i;

[0036] When the communication speed quality index exceeds the preset value, a fault data analysis instruction is generated; when the communication speed quality index does not exceed the preset value, no measures are taken.

[0037] Preferably, the process of collecting fault data includes the following steps:

[0038] Fault identification: Clearly define faults, such as node unresponsiveness, high latency, and high packet loss, and set specific thresholds to ensure the monitoring system can accurately identify and record faults;

[0039] Data sources: Obtain access to monitoring logs and fault report databases to ensure coverage of all geographically distributed nodes and real-time updates;

[0040] Data extraction: Extracting fault time, location, type, and other related information, such as duration, impact range, and recovery time;

[0041] Data validation and cleaning: Verify data integrity, remove duplicate or invalid records, and clean data for subsequent analysis.

[0042] Technical effects and advantages of the present invention:

[0043] (1) The data network-based transmission control method provided by the present invention divides the data network into several geographical areas, and screens and obtains the number of the geographical area with abnormal data transmission according to the communication quality of the geographical area; collects the fault data of the data transmission nodes with the number of the geographical area with abnormal data transmission, and the fault data includes the time and location of each fault; analyzes the fault data to obtain the fault time distribution coefficient and the fault space distribution coefficient; jointly analyzes the fault time distribution coefficient and the fault space distribution coefficient to obtain the transmission performance balance index of the geographical area with abnormal data transmission; guides the geographical area to take measures based on the transmission performance balance index, and solves the problem in the prior art that resource allocation is often based on experience or fixed rules, and it is difficult to achieve optimal configuration and efficient utilization of resources.

[0044] (2) The data network-based transmission control method provided by the present invention uses the failure rate data of each time window and each data transmission node in the historical time period as the input of the failure rate prediction model, and outputs the predicted failure rate in the future time window and at each data transmission node location; screens potential failure data nodes based on the predicted failure rate of each data transmission node location; prompts users to maintain potential failure data nodes; provides users with sufficient time to perform maintenance to avoid losses caused by failures, which can effectively reduce the failure rate of data transmission and improve stability and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a flow chart of the transmission control method of the present invention.

[0046] Figure 2 This is a flow chart for building the failure rate prediction model of the present invention. DETAILED DESCRIPTION

[0047] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0048] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0049] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the present disclosure, its application, or uses.

[0050] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0051] Example 1

[0052] The present invention provides a data network-based transmission control method, comprising:

[0053] Monitor the monitoring log information of the data transmission nodes in each geographical area to obtain the communication upload load, communication downlink load, average communication upload speed, average communication downlink speed, communication upload failure rate, and communication downlink failure rate of each geographical area;

[0054] The communication speed quality index TV_i of the i-th geographical area is obtained by analysis;

[0055] When the communication speed quality index exceeds the preset value, the number of the geographical area with abnormal data transmission is output and a fault data analysis instruction is generated; when the communication speed quality index does not exceed the preset value, no measures are taken.

[0056] In the embodiment of the present invention, which needs further explanation, the process of obtaining the communication speed quality index includes the following steps:

[0057] Collect monitoring log information of data transmission nodes in each geographical area, where i represents the number of geographical areas and n represents the number of geographical areas;

[0058] Obtain the average upload speed and download speed of the i-th geographical area, which are recorded as Us and Ds respectively; obtain the upload failure rate and download failure rate of the i-th geographical area, which are recorded as Uf and Df respectively;

[0059] By formula The basic speed quality Btv_i of the i-th geographical area is calculated, where γ represents the weight factor for adjusting the impact of the failure rate;

[0060] By formula The load reduction factor LP_i of the i-th geographical area is calculated, where λ represents the parameter that controls the shape of the reduction curve; Fth represents the load threshold, exceeding which the communication transmission speed is considered to be affected; LF represents the sum of the upload load and the download load;

[0061] Obtain the communication speed quality index TV_i of the i-th geographical area; calculate the communication speed quality index Tz_i by the formula Tz_i=Btv_i*LP_i;

[0062] When the communication speed quality index exceeds the preset value, a fault data analysis instruction is generated; when the communication speed quality index does not exceed the preset value, no measures are taken.

[0063] Explanation: Based on the fact that speed quality decreases faster under high load, the load attenuation factor is designed; the λ and γ parameters need to be optimized through actual testing to ensure that TV_i can accurately reflect the performance of the communication network.

[0064] Example 2

[0065] See Figure 1 The present invention provides a flow chart of a transmission control method. Figure 1 A data network-based transmission control method is shown, comprising the following steps:

[0066] Step 1: Receive the ID of the data transmission abnormality geographic area, collect fault data of the data transmission nodes in each data transmission abnormality geographic area, the fault data including the time and location of each fault; collect the fault data of all transmission nodes from the monitoring log or fault report of the data network;

[0067] Specifically, the process of collecting fault data includes the following steps:

[0068] Fault identification: Clearly define faults, such as node unresponsiveness, high latency, and high packet loss rate, and set specific thresholds (e.g., latency > X milliseconds, packet loss rate > Y%) to ensure the monitoring system can accurately identify and record faults.

[0069] Data sources: Obtain access to monitoring logs and fault report databases to ensure coverage of all geographically located nodes and enable real-time / regular updates;

[0070] Data extraction: Use SQL, data scraping tools, or APIs to extract the outage time (accurate to minutes / seconds), location (node ID / geographic location), type (hardware / software / network congestion, etc.), and other related information (such as duration, impact range, and recovery time) from the above systems.

[0071] Data storage: Choose a structured database such as MySQL / PostgreSQL, design a table structure to store fault data, including fields such as time, location, and type, import the data, ensure its integrity and accuracy, and set a backup strategy;

[0072] Data validation and cleaning: Verify data integrity, remove duplicate or invalid records, and clean data (such as formatting timestamps and unifying geographic locations) for subsequent analysis.

[0073] Step 2: Analyze the fault data and calculate the ratio of the number of faulty nodes to the total number of nodes at each time point to obtain the fault time distribution coefficient FT; calculate the ratio of the number of faulty nodes at each location to the total number of nodes to obtain the fault space distribution coefficient FK;

[0074] Step 3: Jointly analyze the fault time distribution coefficient and the fault space distribution coefficient, and use the formula Calculate the transmission performance balance index CJ for each geographical area with abnormal data transmission;

[0075] Step 4: Take regulatory measures based on the transmission performance balance index; compare the calculated transmission performance balance index with the preset threshold. When the transmission performance balance index is lower than the threshold, the geographical area with abnormal data transmission will increase resource investment, optimize the network structure, and adjust the load balancing strategy.

[0076] In the embodiment of the present invention, it is necessary to further explain that if the CJ is lower than the preset value, it indicates that the performance of the abnormal data transmission geographical area has significantly deteriorated and immediate intervention measures are required, including but not limited to:

[0077] Increase resource investment: allocate more bandwidth to the area, add transmission nodes or upgrade hardware equipment to improve data transmission capacity; optimize network structure: adjust the network topology to reduce transmission delay and congestion, and improve data transmission efficiency; adjust load balancing strategy: reallocate network traffic to ensure load balance among nodes and avoid overloading of a single node; perform troubleshooting and repair: conduct detailed troubleshooting on specific faulty nodes and locations, repair the fault as soon as possible, and restore normal network operation.

[0078] In the embodiment of the present invention, it is necessary to further explain that if CJ exceeds the preset value, it means that the performance of the area is still within the acceptable range, but its changing trend needs to be continuously monitored. The following measures can be taken to prevent potential problems:

[0079] Regular maintenance and inspection: Data transmission nodes and network infrastructure are regularly maintained and inspected to ensure normal operation. Based on network usage and performance data, the network is fine-tuned and optimized to improve overall performance. Resources are reserved for possible emergencies to enable rapid response when needed.

[0080] In the embodiment of the present invention, it is necessary to further explain that the failure time distribution coefficient is obtained as follows:

[0081] The communication network operation information is divided into several time windows, and the number of faulty nodes in each time window is obtained; suppose there are m time windows, and j represents the sequence number of the time window;

[0082] Let k represent the sequential number of the time points in the time window, and obtain the number of faulty nodes detected at the kth time point; N represents the total number of data transmission nodes, k traverses the time points from time t-w+1 to time t; w represents the number of time points in the time window;

[0083] By formula Calculate the average failure rate Ftd in the jth time window j ; Where Fk represents the number of faulty nodes detected at the kth time point;

[0084] By formula The failure time distribution coefficient is calculated.

[0085] In the embodiment of the present invention, it is necessary to further explain that the fault spatial distribution coefficient is obtained as follows:

[0086] The communication network operation information is divided into several locations according to the data transmission nodes, and the cumulative number of failures F at each location is obtained. P ; Use p to represent the data transmission node position number, Q to represent the total number of data transmission nodes; through the formula Calculate the failure rate of the pth position; by formula The fault spatial distribution coefficient is calculated.

[0087] In the embodiments of the present invention, it is necessary to further explain that if the transmission performance balance index does not exceed the preset value, the current data network performance is considered to be balanced; if it exceeds the preset value, the current data network performance is considered to be unbalanced, and optimization measures are taken, including: adding redundant nodes, optimizing network topology, upgrading hardware equipment, improving environmental conditions, etc.; resource allocation is guided based on the transmission performance balance index, and data transmission problems in performance bottlenecks and high-prone geographical areas are given priority to ensure that resources are used reasonably and effectively.

[0088] Summary: By comprehensively considering the temporal and spatial distribution of fault data, the performance balance of data transmission nodes can be comprehensively and systematically evaluated; this helps to identify potential performance bottlenecks and fault hotspots; by calculating the fault time distribution coefficient and the fault spatial distribution coefficient and jointly analyzing these two coefficients to obtain the transmission performance balance index, a quantitative evaluation of the performance of data transmission nodes is achieved, making the evaluation results more objective and accurate, and facilitating the location of geographical areas with data transmission anomalies; real-time monitoring of communication network operation information and dynamic adjustment of evaluation parameters and thresholds based on the monitoring results. This dynamic monitoring mechanism helps to promptly discover and resolve performance imbalance problems and improve the utilization efficiency of data network monitoring resources.

[0089] Example 3

[0090] The difference between the embodiment of the present invention and embodiment 2 is that the transmission control method includes a data visualization interaction module, which is used to transmit the fault transmission node distribution map and the transmission performance balance index to the user end. The fault transmission node distribution map is obtained by drawing a fault transmission node position distribution map that changes with time; using the collected fault data, the horizontal axis represents time, and the vertical axis represents the position of the transmission node (which can be a physical position or a logical position, such as a node number) to draw a fault time-space two-dimensional map. On the fault time-space two-dimensional map, each fault point is represented by a mark, thereby obtaining a fault transmission node distribution map that changes with time.

[0091] The difference between this embodiment of the present invention and embodiment 2 is that the transmission control method includes the following steps:

[0092] Step 5: Use the failure rate data of each time window and each data transmission node in the historical time period as the input of the failure rate prediction model, and output the predicted failure rate in the future time window and at each data transmission node location;

[0093] Step 6: Screen potential faulty data nodes based on the predicted fault occurrence rate of each data transmission node location; and prompt the user to maintain the potential faulty data nodes.

[0094] See Figure 2 The process of obtaining the failure rate prediction model includes the following steps:

[0095] Step S11, data preparation: collect and organize time series data, including the failure rate of each time window and each location;

[0096] Step S12: Check the data to see if it is stable. If it is not stable, differential transformation is required.

[0097] Step S13, model identification: using the autocorrelation function and the partial autocorrelation function to determine the parameter factors of the ARIMA model;

[0098] Step S14, model fitting: fitting the ARIMA model based on the obtained parameter factors;

[0099] Step S15, model diagnosis: check whether the residuals of the model are random and independent to ensure the validity of the model and obtain a well-fitted fault occurrence rate prediction model;

[0100] Step S16: Prediction: Use the fitted fault occurrence rate prediction model to predict the fault occurrence rate in the next time window and at each location.

[0101] It needs to be further explained in the embodiment of the present invention that the process of obtaining the failure occurrence rate prediction model includes using actual data to verify the accuracy of the prediction and adjusting the failure occurrence rate prediction model as needed.

[0102] In the embodiments of the present invention, further explanation is required. For the screened potential fault data nodes, detailed maintenance prompt information is generated; the maintenance prompt information includes the specific location of the node, the predicted fault rate, the possible fault cause and the recommended maintenance measures; the maintenance prompt information is sent to the relevant users or the operation and maintenance team via email, SMS, system notification, etc.; the user's response to the maintenance prompt is tracked, and feedback information is collected.

[0103] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A data network-based transmission control method, characterized in that: The following steps are involved: Step 1: Receive the ID of the data transmission abnormal geographical area, and collect the fault data of the data transmission nodes in each data transmission abnormal geographical area, wherein the fault data includes the time and location of each fault occurrence; Step 2: Analyze the fault data, calculate the ratio of the number of faulty nodes to the total number of nodes at each time point, and obtain the fault time distribution coefficient FT; Calculate the ratio of the number of faulty nodes at each location to the total number of nodes to obtain the fault spatial distribution coefficient FK; The method for obtaining the failure time distribution coefficient is as follows: divide the communication network operation information into several time windows, and obtain the number of faulty nodes in each time window; suppose there are m time windows, j represents the sequence number of the time window; k represents the sequence number of the time point in the time window, and obtains the number of faulty nodes detected at the kth time point; N represents the total number of data transmission nodes, k traverses the time points from time t-w+1 to time t; w represents the number of time points in the time window; through the formula Calculate the average failure rate Ftd in the jth time window j ; Where Fk represents the number of faulty nodes detected at the kth time point; through the formula Calculate the failure time distribution coefficient; The method for obtaining the fault spatial distribution coefficient is as follows: the communication network operation information is divided into several locations according to the data transmission nodes, and the cumulative number of faults at each location is obtained. P ; Use p to represent the data transmission node position number, Q to represent the total number of data transmission nodes; through the formula Calculate the failure rate of the pth position; by formula The fault spatial distribution coefficient is calculated; Step 3: Jointly analyze the fault time distribution coefficient and the fault space distribution coefficient, and use the formula Calculate the transmission performance balance index CJ of each regional data transmission node; Step 4: Take regulatory measures based on the transmission performance balance index; compare the calculated transmission performance balance index with the preset threshold. When the transmission performance balance index is lower than the threshold, increase resource investment, optimize network structure, and adjust load balancing strategies for geographical areas with abnormal data transmission.

2. A data network-based transmission control method according to claim 1, characterized in that: If the transmission performance balance index is lower than the threshold, it means that the performance of the data transmission abnormality area corresponding to the transmission performance balance index has significantly degraded, and immediate intervention measures are required; If the transmission performance balance index exceeds the threshold, it means that the performance of the geographical area with abnormal data transmission is still within an acceptable range, but its changing trend needs to be continuously monitored.

3. The data network-based transmission control method according to claim 1, characterized in that: The transmission control method includes a data visualization interaction module, which is used to transmit a fault transmission node distribution map and a transmission performance balance index to a user end. The fault transmission node distribution map is obtained by drawing a fault transmission node position distribution map that changes with time; using the collected fault data, the horizontal axis represents time and the vertical axis represents the position of the transmission node to draw a fault time-space two-dimensional map. On the fault time-space two-dimensional map, each fault point is represented by a mark, thereby obtaining a fault transmission node distribution map that changes with time.

4. The data network-based transmission control method according to claim 1, characterized in that: The transmission control method comprises the following steps: Step 5: Use the failure rate data of each time window and each data transmission node in the historical time period as the input of the failure rate prediction model, and output the predicted failure rate in the future time window and at each data transmission node location; Step 6: Screen potential faulty data nodes based on the predicted fault occurrence rate of each data transmission node location; and prompt the user to maintain the potential faulty data nodes.

5. The data network-based transmission control method according to claim 4, characterized in that: The process of obtaining the failure rate prediction model includes the following steps: Step S11, data preparation: collect and organize time series data, including the failure rate of each time window and each location; Step S12: Check the data to see if it is stable. If it is not stable, differential transformation is required. Step S13, model identification: using the autocorrelation function and the partial autocorrelation function to determine the parameter factors of the ARIMA model; Step S14, model fitting: fitting the ARIMA model based on the obtained parameter factors; Step S15, model diagnosis: check whether the residuals of the model are random and independent to ensure the validity of the model and obtain a well-fitted fault occurrence rate prediction model; Step S16, prediction: using the fitted fault incidence prediction model to predict the fault incidence in the next time window and at each location; Step S17, verification and feedback: Use actual data to verify the accuracy of the prediction and adjust the failure rate prediction model as needed.

6. The data network-based transmission control method according to claim 1, characterized in that: The method for obtaining the geographical area number of the data transmission anomaly is as follows: Collect monitoring log information of data transmission nodes in each geographical area, where i represents the number of geographical areas and n represents the number of geographical areas; Obtain the average upload speed and download speed of the i-th geographical area, which are recorded as Us and Ds respectively; obtain the upload failure rate and download failure rate of the i-th geographical area, which are recorded as Uf and Df respectively; By formula The basic speed quality Btv_i of the i-th geographical area is calculated, where γ represents the weight factor for adjusting the impact of the failure rate; By formula The load reduction factor LP_i of the i-th geographical area is calculated, where λ represents the parameter that controls the shape of the reduction curve; Fth represents the load threshold, exceeding which the communication transmission speed is considered to be affected; LF represents the sum of the upload load and the download load; Obtain the communication speed quality index TV_i of the i-th geographical area; calculate the communication speed quality index Tz_i by the formula Tz_i=Btv_i*LP_i; When the communication speed quality index exceeds the preset value, a fault data analysis instruction is generated; when the communication speed quality index does not exceed the preset value, no action is taken.

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