Self-service terminal data synchronization optimization method and system based on feature analysis

Abstract

The present invention discloses a method and system for optimizing data synchronization of self-service terminals based on feature analysis, which relates to fields related to data processing. The method includes: obtaining the synchronization data port, data features, and access records of the self-service terminal; identifying data synchronization features; performing relationship analysis among time synchronization dimension, network transmission dimension, and user access dimension to obtain conflict relationships; performing conflict relationship and abnormal synchronization information search according to the data synchronization log to obtain conflict relationship record information and abnormal synchronization record information; performing conditional probability calculation to output the abnormal probability of the conflict relationship; performing balanced identification and optimization of the synchronization strategy of each synchronization resource on the synchronization data port, and outputting the data synchronization strategy result for synchronization control. The method solves the technical problem that the existing data synchronization strategy lacks flexibility, resulting in low efficiency and insufficient accuracy, and achieves the technical effect of improving efficiency and accuracy by flexibly adjusting the strategy according to data synchronization requirements.

Description

Technical Field

[0001] The present application relates to data processing related fields, and in particular to a method and system for optimizing data synchronization of self-service terminals based on feature analysis. Background Art

[0002] With the rapid development of information technology, self-service terminals are increasingly being used across various industries, such as bank ATMs, self-service ticket vending machines, and self-service payment machines. These terminals require frequent data synchronization with backend servers to ensure data accuracy and consistency. In practice, the data synchronization process is often affected by various factors, such as time delays, network fluctuations, and user access conflicts. These factors can cause data synchronization failures or anomalies, impacting the normal operation of the self-service terminal and user experience. Existing technologies typically use fixed synchronization strategies, such as scheduled synchronization and triggered synchronization. These strategies lack flexibility and cannot be dynamically adjusted based on actual synchronization needs and network environments, resulting in low synchronization efficiency and wasted resources.

[0003] In the current related technologies, the data synchronization of self-service terminals has the technical problem of lack of flexibility in synchronization strategy, resulting in low synchronization efficiency and insufficient synchronization accuracy. Summary of the Invention

[0004] The present application provides a self-service terminal data synchronization optimization method and system based on feature analysis, which obtains the synchronization data port, data features, access records and other information of the self-service terminal, identifies the data synchronization features, performs relationship analysis of the time synchronization dimension, network transmission dimension, and user access dimension, obtains the conflict relationship, uses the data synchronization log to search for conflict relationships and abnormal synchronization information, outputs the abnormal probability of the conflict relationship through conditional probability calculation, performs synchronization strategy balance identification and optimization on the synchronization data port according to the abnormal probability, outputs the optimal data synchronization strategy result for synchronization control and other technical means, and achieves the technical effect of flexibly adjusting the synchronization strategy according to the data synchronization requirements, thereby improving the synchronization efficiency and synchronization accuracy.

[0005] The present application provides a method for optimizing data synchronization of a self-service terminal based on feature analysis, comprising: obtaining a synchronization data port, data features, and access records of the self-service terminal; identifying data synchronization features based on the synchronization data port, data features, and access records; performing relationship analysis among time synchronization dimensions, network transmission dimensions, and user access dimensions based on the data synchronization features to obtain conflict relationships; performing a search for conflict relationships and abnormal synchronization information based on the data synchronization log of the self-service terminal to obtain conflict relationship record information and abnormal synchronization record information; performing conditional probability calculation based on the conflict relationship record information and the abnormal synchronization record information to output an abnormal probability of the conflict relationship; performing balanced identification and optimization of the synchronization strategy of each synchronization resource of the synchronization data port of the self-service terminal based on the abnormal probability of the conflict relationship, outputting a data synchronization strategy result, and performing synchronization control of the self-service terminal based on the data synchronization strategy result.

[0006] In a possible implementation, the relationship between the time synchronization dimension, the network transmission dimension, and the user access dimension is analyzed according to the data synchronization characteristics to obtain the conflict relationship, and the following processing is performed: the dimension relationship is aligned according to the time synchronization dimension, the network transmission dimension, and the user access dimension respectively; based on the alignment relationship, the synchronization cross-resources are extracted, and the synchronization cross-resources are the resources commonly occupied by various types of synchronization data in the self-service terminal; based on the usage load status of the synchronization cross-resources, the conflict points are searched, and the conflict points are synchronization usage nodes whose synchronization cross-resource occupancy ratio exceeds the load threshold and the synchronization efficiency decreases; a mapping association is established between the conflict point and the relationship dimension and the resource load ratio to obtain the conflict relationship.

[0007] In a possible implementation method, dimension relationship alignment is performed according to the time synchronization dimension, network transmission dimension, and user access dimension, and the following processing is performed: key feature parameters of the time synchronization dimension, network transmission dimension, and user access dimension are configured, where the key feature parameters include time window and synchronization frequency; key feature identification and labeling of the data synchronization features are performed according to the key feature parameters; and corresponding relationship dimension alignment is performed according to the key feature labeling.

[0008] In a possible implementation, a conditional probability calculation is performed based on the conflict relationship record information and the abnormal synchronization record information, and the abnormal probability of the conflict relationship is output, and the following processing is performed: based on the conflict relationship record information, the probability of conflict occurrence is calculated; based on the conflict relationship record information and the abnormal synchronization record information, the probability of simultaneous occurrence is calculated; based on the conflict occurrence probability and the simultaneous occurrence probability, the abnormal probability of the conflict relationship is obtained by calculating through the conditional probability formula.

[0009] In a possible implementation, the synchronization strategy balance identification and optimization of each synchronization resource of the synchronization data port of the self-service terminal is performed according to the abnormal probability of the conflict relationship, and the data synchronization strategy result is output, and the following processing is performed: according to the abnormal probability of the conflict relationship, the conflict relationship balance weight is configured; based on the abnormal probability of the conflict relationship, the first conflict relationship strategy combination, the second conflict relationship strategy combination, and the Nth conflict relationship strategy combination are obtained, where N is the number of conflict relationships; according to the conflict relationship balance weight, the first conflict relationship strategy combination, the second conflict relationship strategy combination, and the Nth conflict relationship strategy combination are balanced and identified to obtain the data synchronization strategy result.

[0010] In a possible implementation, based on the abnormal probability of the conflict relationship, the first conflict relationship strategy combination, the second conflict relationship strategy combination, and the Nth conflict relationship strategy combination are obtained, and the following processing is performed: conflict relationship compensation analysis is performed according to the conflict relationship to determine the compensation direction and compensation parameters; the dimensional parameters of the conflict relationship are searched and mutated according to the compensation direction and compensation parameters to obtain the conflict relationship strategy combination.

[0011] In a possible implementation method, the first conflict relationship strategy combination, the second conflict relationship strategy combination, and the Nth conflict relationship strategy combination are balanced and identified according to the conflict relationship balance weight to obtain the data synchronization strategy result, and the following processing is performed: a cost function for each conflict relationship is established; the conflict relationship strategy combination is balanced based on the cost function of the conflict relationship; an evaluation function of the self-service terminal is established, and the evaluation function is used to evaluate the strategy cost of the first conflict relationship strategy combination, the second conflict relationship strategy combination, and the Nth conflict relationship strategy combination; the strategy cost evaluation is minimized based on the conflict relationship balance weight to obtain the data synchronization strategy result.

[0012] The present application also provides a self-service terminal data synchronization optimization system based on feature analysis, including: a data record acquisition module, used to obtain the synchronization data port, data features, and access records of the self-service terminal; a data synchronization feature identification module, used to identify data synchronization features based on the synchronization data port, data features, and access records; a conflict relationship acquisition module, used to perform relationship analysis of time synchronization dimension, network transmission dimension, and user access dimension based on the data synchronization features to obtain conflict relationships; an information search module, used to perform conflict relationship and abnormal synchronization information search based on the data synchronization log of the self-service terminal to obtain conflict relationship record information and abnormal synchronization record information; a conditional probability calculation module, used to perform conditional probability calculation based on the conflict relationship record information and the abnormal synchronization record information, and output the abnormal probability of the conflict relationship; a synchronization strategy balance identification and optimization module, used to perform synchronization strategy balance identification and optimization of each synchronization resource of the synchronization data port of the self-service terminal based on the abnormal probability of the conflict relationship, output the data synchronization strategy result, and use the data synchronization strategy result to perform synchronization control of the self-service terminal.

[0013] The self-service terminal data synchronization optimization method and system based on feature analysis proposed in this application first obtains the synchronization data port, data features, and access records of the self-service terminal, and then identifies the data synchronization features based on the synchronization data port, data features, and access records. Then, the relationship between the time synchronization dimension, network transmission dimension, and user access dimension is analyzed based on the data synchronization features to obtain the conflict relationship. Then, the conflict relationship and abnormal synchronization information are searched based on the data synchronization log of the self-service terminal to obtain the conflict relationship record information and abnormal synchronization record information. Then, the conditional probability calculation is performed based on the conflict relationship record information and the abnormal synchronization record information, and the abnormal probability of the conflict relationship is output. Finally, based on the abnormal probability of the conflict relationship, the synchronization strategy of each synchronization resource of the synchronization data port of the self-service terminal is balanced and optimized, and the data synchronization strategy result is output. The synchronization control of the self-service terminal is performed based on the data synchronization strategy result, thereby achieving the technical effect of flexibly adjusting the synchronization strategy according to the data synchronization requirements, thereby improving the synchronization efficiency and synchronization accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention are briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in precise order. Instead, various steps may be processed in reverse order or simultaneously as needed. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0015] Figure 1A flowchart of a method for optimizing data synchronization of self-service terminals based on feature analysis provided in an embodiment of the present application.

[0016] Figure 2 A structural diagram of a self-service terminal data synchronization optimization system based on feature analysis provided in an embodiment of the present application.

[0017] Explanation of the reference numerals: data record acquisition module 10 , data synchronization feature recognition module 20 , conflict relationship acquisition module 30 , information search module 40 , conditional probability calculation module 50 , synchronization strategy balance recognition and optimization module 60 . DETAILED DESCRIPTION

[0018] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0019] In order to make the purpose, technical solutions and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0020] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict, and the terms “first\second” involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. The terms “including” and “having” and any variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or that are inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used herein are for the purpose of describing the embodiments of this application only.

[0021] The embodiment of the present application provides a self-service terminal data synchronization optimization method based on feature analysis, such as Figure 1 As shown, the method includes:

[0022] Step S100: Acquire the synchronization data port, data characteristics, and access records of the self-service terminal.

[0023] Specifically, monitoring systems or log collection tools are used to collect synchronization data port information (such as port number and communication protocol), data characteristics (information describing data attributes, such as data type, data format, and data size), and access records (recording user access information such as access time, access frequency, and accessing user) from self-service terminals. This data is captured from the self-service terminals periodically or in real time and stored in a central database or log file for subsequent analysis. The synchronization data port refers to the communication interface used by the self-service terminal for data synchronization.

[0024] Step S200: Identify data synchronization features based on the synchronization data port, data features, and access records.

[0025] Specifically, data mining and machine learning algorithms are used to process and analyze the collected data to extract characteristics such as periodicity, concurrency, and data flow of data synchronization. The data synchronization characteristics are information that describes the regularity, periodicity, concurrency, and other characteristics exhibited during the data synchronization process. For example, through association rule mining, it can be found that the frequency of data synchronization increases significantly during certain time periods, which means that this time period is the peak period of user access and the synchronization strategy needs to be optimized to cope with high concurrent access. For example, through cluster analysis, similar data synchronization features can be clustered into one category for subsequent targeted optimization processing. The data synchronization features obtained from the analysis are summarized and organized to form a structured feature representation, including the creation of feature vectors, feature matrices, or feature graphs.

[0026] Step S300 , performing relationship analysis on the time synchronization dimension, the network transmission dimension, and the user access dimension according to the data synchronization characteristics to obtain conflict relationships.

[0027] Specifically, based on data synchronization characteristics, we analyze relationships across three dimensions: time, network transmission, and user access. Through comparative and correlation analysis, we identify factors that may lead to data synchronization conflicts. The time synchronization dimension refers to the scheduling and planning of data synchronization. The network transmission dimension refers to the performance and stability of network transmission during data synchronization. The user access dimension refers to user access behavior and patterns at the self-service terminals.

[0028] In one possible implementation, the relationship between the time synchronization dimension, the network transmission dimension, and the user access dimension is analyzed based on the data synchronization characteristics to obtain conflict relationships. Step S300 further includes step S310, in which the dimensional relationships are aligned according to the time synchronization dimension, the network transmission dimension, and the user access dimension. Specifically, data preprocessing tools or scripts are used to clean, convert, and format the raw data. The collected synchronization data from the self-service terminals is classified according to the time synchronization dimension (e.g., the specific time point or time period when synchronization occurs), the network transmission dimension (e.g., network bandwidth usage, network latency, etc.), and the user access dimension (e.g., the number of visiting users, access frequency, access patterns, etc.). Then, a data alignment algorithm is used to ensure that the data in different dimensions correspond to each other, forming a unified data view.

[0029] In step S320, based on the alignment, cross-synchronization resources are extracted. These resources are shared by various types of synchronized data on the self-service terminal. Specifically, resource monitoring tools or custom scripts are used to collect real-time or periodic information about the self-service terminal's resource usage, including CPU usage, memory usage, and disk I / O. Based on the data alignment, data analysis algorithms are used to identify resources shared by multiple synchronized tasks or users. These resources are considered cross-synchronization resources.

[0030] Step S330 searches for conflict points based on the cross-synchronization resource usage load. These conflict points are synchronization nodes where the cross-synchronization resource occupancy ratio exceeds a load threshold and synchronization efficiency decreases. Specifically, a load threshold is set. When the cross-synchronization resource usage load exceeds this threshold, a conflict detection mechanism is triggered. The conflict detection algorithm analyzes the execution logs and performance data of synchronization tasks to identify synchronization nodes where synchronization efficiency has significantly decreased. These nodes are considered conflict points.

[0031] Step S340 maps the conflict points to the relationship dimensions and resource load ratios to obtain the conflict relationships. Specifically, using data analysis software or tools, relevant information about the conflict points (such as the time of occurrence, involved network parameters, user access patterns, and resource load ratios) is integrated and analyzed to form a conflict relationship map. This map intuitively displays the relationship between the conflict points and different dimensions (time synchronization, network transmission, and user access), as well as the impact of the conflict on the data synchronization performance of the self-service terminal. This implementation method accurately identifies potential conflict points and bottlenecks by comprehensively analyzing various factors (time, network, and user access) and resource usage during the self-service terminal data synchronization process, providing a scientific basis for developing effective data synchronization strategies.

[0032] In one possible implementation, dimensional relationship alignment is performed according to the time synchronization dimension, network transmission dimension, and user access dimension, and step 310 further includes step S311, configuring key characteristic parameters of the time synchronization dimension, network transmission dimension, and user access dimension, wherein the key characteristic parameters include a time window and a synchronization frequency. Specifically, in the time synchronization dimension, a time window is set, i.e., a time range or period for data synchronization, and a time point or frequency for synchronization. In the network transmission dimension, a synchronization frequency is set, i.e., a frequency of data transmission between different nodes or systems. In the user access dimension, parameters such as the mode, frequency, and peak period of user access are set.

[0033] Step S312: Key feature identification and labeling of the data synchronization features based on key feature parameters. Specifically, a preset algorithm or model is used to identify the data synchronization features based on key feature parameters such as time window and synchronization frequency. The identified key features are labeled to facilitate subsequent alignment of the corresponding dimensions.

[0034] Step S313, align the corresponding relationship dimensions according to the key feature identifier. Specifically, according to the key feature identifier, the features of the time synchronization dimension, the network transmission dimension and the user access dimension are corresponded and matched. Ensure that the data and information between each dimension are consistent, and can correspond and relate to each other. This implementation method ensures the accuracy and efficiency of data synchronization by configuring key feature parameters. Through key feature identification and marking, features with important influence or representativeness can be screened out from a large number of data synchronization features. Through corresponding relationship dimension alignment, it ensures that the data and information between each dimension are consistent, and can correspond and relate to each other, which helps to discover conflicts and anomalies in the data synchronization process.

[0035] Step S400 : searching for conflict relationship and abnormal synchronization information based on the data synchronization log of the self-service terminal to obtain conflict relationship record information and abnormal synchronization record information.

[0036] Specifically, log analysis tools are used to deeply mine the self-service terminal's data synchronization logs (log files that record various events and statuses that occur during the self-service terminal's data synchronization process). Log data is filtered, classified, and statistically analyzed to identify and extract conflict relationships and abnormal synchronization information. This refers to information about conflict events recorded by the self-service terminal during data synchronization, including the conflict type, occurrence time, and the data involved. Abnormal synchronization records refer to information about abnormal events recorded by the self-service terminal during data synchronization, such as synchronization failures and data corruption.

[0037] Step S500 : performing conditional probability calculation based on the conflict relationship record information and the abnormal synchronization record information, and outputting the abnormal probability of the conflict relationship.

[0038] Specifically, the conditional probability calculation method in statistics is used to process the conflict relationship record information and the abnormal synchronization record information, calculate the probabilities of conflict and abnormal events, evaluate their correlation, and calculate the abnormal probability of the conflict relationship, that is, the probability that the conflict relationship leads to the occurrence of abnormal synchronization events.

[0039] In one possible implementation, a conditional probability calculation is performed based on the conflict relationship record information and the abnormal synchronization record information to output the abnormal probability of the conflict relationship. Step S500 further includes step S510, which calculates the probability of conflict occurrence based on the conflict relationship record information. Specifically, the conflict relationship record information is organized and analyzed. The conflict relationship record information includes various types of conflict events, such as data inconsistency, synchronization timeout, and data loss. For each conflict event, its frequency of occurrence in the record is counted. Then, by dividing these frequencies by the total number of conflict events, the probability of each conflict event occurring, i.e., the probability of conflict occurrence, is obtained.

[0040] Step S520 calculates the probability of simultaneous occurrence based on the conflict relationship record information and the abnormal synchronization record information. Specifically, considering both the conflict relationship record information and the abnormal synchronization record information, first, identify which conflict events and abnormal synchronization events are related, i.e., they are caused by the same root cause. Then, for each pair of related events, count the number of simultaneous occurrences. Finally, by dividing this number by the total number of records, the probability of these events occurring simultaneously, i.e., the simultaneous occurrence probability, is calculated.

[0041] Step S530, based on the probability of conflict occurrence and the probability of simultaneous occurrence, the abnormal probability of the conflict relationship is calculated by the conditional probability formula. Specifically, the abnormal probability of the conflict relationship is calculated using the conditional probability formula, which is P(A|B)=P(A,B) / P(B), where P(A|B) represents the probability of event A occurring under the condition that event B occurs, P(A,B) represents the probability of event A and event B occurring simultaneously, and P(B) represents the probability of event B occurring. Here, the abnormal synchronization event is event A, and the conflict event is event B. Then, the probability of conflict occurrence and the probability of simultaneous occurrence calculated in steps S510 and S520 are substituted into the conditional probability formula for calculation to obtain the abnormal probability of the conflict relationship, that is, the probability that the abnormal synchronization event also occurs under the condition that the conflict event occurs, which is used to evaluate the correlation between the conflict event and the abnormal synchronization event.

[0042] Step S600 , performing synchronization strategy balance identification and optimization of each synchronization resource on the synchronization data port of the self-service terminal according to the abnormal probability of the conflict relationship, outputting a data synchronization strategy result, and performing synchronization control of the self-service terminal based on the data synchronization strategy result.

[0043] Specifically, based on the abnormal probability of the conflict relationship, the synchronization data port of the self-service terminal is optimized, and the data synchronization strategy is adjusted, such as adjusting the synchronization frequency, optimizing the network transmission path, and restricting user access, so as to reduce the occurrence of conflicts and abnormalities and achieve balanced allocation and efficient utilization of synchronization resources. Among them, the synchronization strategy balance identification optimization refers to optimizing the synchronization strategy through an algorithm or model to achieve balanced allocation and efficient utilization of resources. The data synchronization strategy result is an optimized data synchronization strategy, which is used to guide the synchronization control of the self-service terminal. The embodiment of the present application adopts the following technical means: obtaining the synchronization data port, data characteristics, access records and other information of the self-service terminal, identifying the data synchronization characteristics, parsing the relationship between the time synchronization dimension, network transmission dimension, and user access dimension, obtaining the conflict relationship, searching for the conflict relationship and abnormal synchronization information using the data synchronization log, outputting the abnormal probability of the conflict relationship through conditional probability calculation, performing synchronization strategy balance identification optimization on the synchronization data port according to the abnormal probability, outputting the optimal data synchronization strategy result for synchronization control, etc., achieving the technical effect of flexibly adjusting the synchronization strategy according to the data synchronization requirements, thereby improving the synchronization efficiency and synchronization accuracy.

[0044] In one possible implementation, synchronization policy balancing and optimization are performed on the synchronization data port of the self-service terminal based on the abnormal probability of the conflict relationship, and a data synchronization policy result is output. Step S600 further includes step S610, which configures a conflict relationship balancing weight based on the abnormal probability of the conflict relationship. Specifically, the abnormal probability of the conflict relationship represents the strength of the correlation between the conflict event and the abnormal synchronization event. A higher abnormal probability indicates a stronger correlation between the conflict event and the abnormal synchronization event, potentially having a greater impact on the stability and efficiency of data synchronization. Based on this understanding, a balancing weight is assigned to each conflict relationship. This weight is determined based on the abnormal probability of the conflict relationship and is used to measure the impact of different conflict relationships on the stability and efficiency of data synchronization. Various methods can be used to assign weights, such as linear mapping, nonlinear mapping, and piecewise functions. For example, a threshold can be set, and when the abnormal probability is above the threshold, a higher weight is assigned; when the abnormal probability is below the threshold, a lower weight is assigned. Alternatively, a function can be designed so that the weight changes smoothly with the abnormal probability.

[0045] Step S620, based on the abnormal probability of the conflict relationship, obtain the first conflict relationship strategy combination, the second conflict relationship strategy combination, and up to the Nth conflict relationship strategy combination, where N is the number of conflict relationships. Specifically, a variety of possible resolution strategies are designed for each conflict relationship, which may be adjusting the synchronization time interval, optimizing the network transmission path, restricting user access rights, etc. Then, based on the abnormal probability of the conflict relationship, the most appropriate strategy combination is selected for each conflict relationship. For example, for a conflict relationship with a higher abnormal probability, a more radical or more comprehensive resolution strategy can be selected; for a conflict relationship with a lower abnormal probability, a more conservative or more local strategy can be selected. Finally, a strategy combination is generated for each conflict relationship, and these combinations are used as inputs for subsequent equilibrium identification. Among them, the conflict relationship strategy combination is a collection of multiple possible solutions designed for a specific conflict relationship, which is used to optimize the data synchronization process.

[0046] Step S630, balance identification is performed on the first conflict relationship strategy combination, the second conflict relationship strategy combination, and up to the Nth conflict relationship strategy combination according to the conflict relationship balance weight, to obtain the data synchronization strategy result. Specifically, the conflict relationship balance weight is used to evaluate the comprehensive effect of different strategy combinations, and the weighted sum or weighted average of each strategy combination is calculated, and the strategy combination with the highest weighted sum or weighted average is selected as the data synchronization strategy result. This implementation method can more accurately optimize the data synchronization process by assigning balance weights to different conflict relationships and selecting the optimal strategy combination based on these weights, which not only improves the stability and efficiency of data synchronization, but also reduces unnecessary resource waste and the occurrence of conflict events.

[0047] In one possible implementation, based on the abnormal probability of the conflict relationship, a first conflict relationship strategy combination, a second conflict relationship strategy combination, and up to the Nth conflict relationship strategy combination are obtained, and step S620 further includes step S621, performing conflict relationship compensation analysis according to the conflict relationship to determine the compensation direction and compensation parameters. Specifically, an in-depth analysis is performed on the conflict relationship to identify the root causes of the conflict, including deviations in time synchronization, bottlenecks in network transmission, abnormalities in user access patterns, and other aspects. Once the cause of the conflict is identified, the direction of compensation can be determined, that is, the specific aspects to which the compensation measures are directed, such as time synchronization, network transmission, user access, etc. For example, if the conflict is caused by network congestion, the compensation direction can be to optimize the network transmission path or adjust the data packet size. After determining the compensation direction, specific compensation parameters are set. These parameters can quantitatively describe the degree of compensation, such as the degree of optimization of the network transmission path, the adjustment range of the data packet size, etc.

[0048] In step S622, the conflict relationship's dimensional parameters are searched and mutated based on the compensation direction and compensation parameters to obtain a conflict relationship strategy combination. Specifically, based on the compensation direction and compensation parameters determined in step S621, the conflict relationship's dimensional parameters are searched and mutated to generate possible conflict relationship strategy combinations. Specifically, the dimensional parameters eligible for search and mutation are identified. These parameters are closely related to the conflict relationship's compensation direction, such as the time synchronization interval, network transmission rate, and user access permissions. Next, these dimensional parameters are searched and mutated using a search and mutation algorithm (such as a genetic algorithm or simulated annealing algorithm). These algorithms can automatically find optimal or near-optimal solutions within a given search space. Through this search and mutation algorithm, multiple possible conflict relationship strategy combinations are generated. These combinations serve as input for equilibrium identification in subsequent steps. This implementation method systematically explores the space of possible solutions through conflict relationship compensation analysis and dimensional parameter search and mutation, thereby finding the optimal or near-optimal strategy combination for a specific conflict relationship, improving the targetedness and effectiveness of the solution.

[0049] In one possible implementation, the first conflict relationship strategy combination, the second conflict relationship strategy combination, and so on, are identified for balance based on the conflict relationship balance weights to obtain the data synchronization strategy results. Step S630 further includes step S631, where a cost function is established for each conflict relationship. Specifically, a cost function is established for each conflict relationship to quantify the negative impact of the conflict relationship on the data synchronization process. A cost function is a mathematical expression that calculates a value based on specific characteristics of the conflict relationship (such as time delay, data loss rate, network congestion, etc.). This value reflects the negative impact of the conflict relationship. Therefore, key features must first be extracted from the conflict relationship records and abnormal synchronization records. These features can accurately reflect the nature and severity of the conflict relationship. Then, based on the extracted features, a cost function is designed. This function can reflect the balance of strategies within the conflict relationship and map these features to a single value. A smaller value indicates a better balance of the conflict relationship achieved by the strategy combination, and vice versa. Finally, the cost function parameters are tuned through experiments or simulations to ensure that it accurately reflects the actual impact of the conflict relationship.

[0050] Step S632: Balancing the conflicting strategy combinations based on the conflicting cost function. Specifically, initial parameter values ​​are set for the conflicting strategy combinations, and the optimization algorithm is used to iteratively adjust the strategy combination parameters. Each iteration calculates the output of the cost function and adjusts the parameters accordingly until convergence conditions are met (e.g., the cost function value no longer decreases significantly).

[0051] Step S633 establishes an evaluation function for the self-service terminal. This evaluation function is used to evaluate the policy costs of the first conflicting policy combination, the second conflicting policy combination, and so on, up to the Nth conflicting policy combination. Specifically, a comprehensive evaluation method is used to establish an evaluation function for the self-service terminal. This evaluation function is a mathematical expression that quantifies the overall synchronization cost of the self-service terminal. It integrates the costs of multiple conflicting relationships and other performance indicators of the self-service terminal, such as synchronization success rate and synchronization speed. The output of this expression is a numerical value that quantifies the overall synchronization effect of the self-service terminal. A smaller numerical value indicates a lower cost for the policy combination and a better overall effect.

[0052] Step S634, based on the conflict relationship balance weight, the policy cost evaluation is minimized and searched to obtain the data synchronization policy result. Specifically, during the search process, the influence of the conflict relationship balance weight on the policy cost evaluation is considered. These weights reflect the relative importance of different conflict relationships. A search algorithm is used to search in the policy space. Each search calculates the policy cost evaluation (i.e., the output value of the evaluation function), and the search direction is adjusted according to the output value and the conflict relationship balance weight until a policy combination that minimizes the output value of the evaluation function is found. The optimal policy combination found is output as the data synchronization policy result. This implementation method ensures that a good policy equilibrium state is achieved within each conflict relationship by establishing a cost function and optimizing the policy combination. By establishing an evaluation function and performing a minimization search, the costs of multiple conflict relationships and the overall synchronization effect of the self-service terminal are comprehensively considered to find the optimal data synchronization policy result, ensuring that the best trade-off point is found between multiple conflict relationships and achieving the optimization of the overall synchronization effect.

[0053] In the above, refer to Figure 1 The self-service terminal data synchronization optimization method based on feature analysis according to an embodiment of the present invention is described in detail. Figure 2 A self-service terminal data synchronization optimization system based on feature analysis according to an embodiment of the present invention is described.

[0054] The feature-analysis-based self-service terminal data synchronization optimization system according to an embodiment of the present invention is designed to address the technical issues of existing self-service terminal data synchronization, such as a lack of flexibility in synchronization strategies, resulting in low synchronization efficiency and insufficient synchronization accuracy. This system achieves the technical effect of improving synchronization efficiency and accuracy by flexibly adjusting synchronization strategies based on data synchronization requirements. The feature-analysis-based self-service terminal data synchronization optimization system includes a data record acquisition module 10, a data synchronization feature identification module 20, a conflict relationship acquisition module 30, an information search module 40, a conditional probability calculation module 50, and a synchronization strategy balance identification and optimization module 60.

[0055] The data record acquisition module 10 is used to obtain the synchronization data port, data characteristics, and access records of the self-service terminal; the data synchronization characteristic identification module 20 is used to identify the data synchronization characteristics based on the synchronization data port, data characteristics, and access records; the conflict relationship acquisition module 30 is used to perform relationship analysis of the time synchronization dimension, network transmission dimension, and user access dimension based on the data synchronization characteristics to obtain the conflict relationship; the information search module 40 is used to search for conflict relationships and abnormal synchronization information based on the data synchronization log of the self-service terminal to obtain conflict relationship record information and abnormal synchronization record information; the conditional probability calculation module 50 is used to perform conditional probability calculation based on the conflict relationship record information and the abnormal synchronization record information, and output the abnormal probability of the conflict relationship; the synchronization strategy balance identification and optimization module 60 is used to perform synchronization strategy balance identification and optimization of each synchronization resource of the synchronization data port of the self-service terminal based on the abnormal probability of the conflict relationship, output the data synchronization strategy result, and use the data synchronization strategy result to perform synchronization control of the self-service terminal.

[0056] The specific configuration of the conflict relationship acquisition module 30 will be described in detail below. As described above, the relationship between the time synchronization dimension, the network transmission dimension, and the user access dimension is analyzed according to the data synchronization characteristics to obtain the conflict relationship. The conflict relationship acquisition module 30 may further include: a dimension relationship alignment unit for performing dimension relationship alignment according to the time synchronization dimension, the network transmission dimension, and the user access dimension respectively; a synchronization cross resource extraction unit for extracting synchronization cross resources based on the alignment relationship, wherein the synchronization cross resources are resources commonly occupied by various types of synchronization data in the self-service terminal; a conflict point search unit for searching for conflict points based on the usage load status of the synchronization cross resources, wherein the conflict point is a synchronization usage node whose synchronization cross resource occupancy ratio exceeds the load threshold and whose synchronization efficiency decreases; a mapping association establishment unit for establishing a mapping association between the conflict point and the relationship dimension and the resource load ratio to obtain the conflict relationship.

[0057] Among them, dimension relationship alignment is performed respectively according to the time synchronization dimension, network transmission dimension, and user access dimension, and the dimension relationship alignment unit may further include: a key feature parameter configuration subunit for configuring the key feature parameters of the time synchronization dimension, network transmission dimension, and user access dimension, wherein the key feature parameters include a time window and a synchronization frequency; a key feature identification subunit for identifying and labeling the key features of the data synchronization features according to the key feature parameters; and a dimension alignment subunit for performing corresponding relationship dimension alignment according to the key feature identification.

[0058] The specific configuration of the conditional probability calculation module 50 will be described in detail below. As described above, the conditional probability calculation module 50 performs conditional probability calculation based on the conflict relationship record information and the abnormal synchronization record information, and outputs the abnormal probability of the conflict relationship. The conditional probability calculation module 50 may further include: a conflict occurrence probability calculation unit for calculating the conflict occurrence probability based on the conflict relationship record information; a simultaneous occurrence probability calculation unit for calculating the simultaneous occurrence probability based on the conflict relationship record information and the abnormal synchronization record information; and an abnormal probability calculation unit for calculating the abnormal probability of the conflict relationship using a conditional probability formula based on the conflict occurrence probability and the simultaneous occurrence probability.

[0059] The specific configuration of the synchronization strategy balance identification and optimization module 60 will be described in detail below. As described above, the synchronization strategy balance identification and optimization module 60 performs synchronization strategy balance identification and optimization on the synchronization data port of the self-service terminal according to the abnormal probability of the conflict relationship, and outputs the data synchronization strategy result. The synchronization strategy balance identification and optimization module 60 may further include: a conflict relationship balance weight configuration unit for configuring the conflict relationship balance weight according to the abnormal probability of the conflict relationship; a conflict relationship strategy combination acquisition unit for obtaining a first conflict relationship strategy combination, a second conflict relationship strategy combination, and up to the Nth conflict relationship strategy combination based on the abnormal probability of the conflict relationship, where N is the number of conflict relationships; and a balance identification unit for performing balance identification on the first conflict relationship strategy combination, the second conflict relationship strategy combination, and up to the Nth conflict relationship strategy combination according to the conflict relationship balance weight to obtain the data synchronization strategy result.

[0060] Among them, based on the abnormal probability of the conflict relationship, the first conflict relationship strategy combination, the second conflict relationship strategy combination, and up to the Nth conflict relationship strategy combination are obtained, and the conflict relationship strategy combination acquisition unit may further include: a conflict relationship compensation analysis subunit for performing conflict relationship compensation analysis according to the conflict relationship, and determining the compensation direction and compensation parameters; a dimension parameter search mutation subunit for performing dimension parameter search and mutation of the conflict relationship according to the compensation direction and compensation parameters to obtain the conflict relationship strategy combination.

[0061] Among them, the first conflict relationship strategy combination, the second conflict relationship strategy combination, and the Nth conflict relationship strategy combination are balanced and identified according to the conflict relationship balance weight to obtain the data synchronization strategy result. The balance identification unit may further include: a cost function establishment subunit for establishing the cost function of each conflict relationship; a conflict relationship strategy combination balancing subunit for balancing the conflict relationship strategy combination based on the cost function of the conflict relationship; a strategy cost evaluation subunit for establishing an evaluation function of the self-service terminal, and using the evaluation function to evaluate the strategy cost of the first conflict relationship strategy combination, the second conflict relationship strategy combination, and the Nth conflict relationship strategy combination; a minimization search subunit for performing a minimization search on the strategy cost evaluation based on the conflict relationship balance weight to obtain the data synchronization strategy result.

[0062] The self-service terminal data synchronization optimization system based on feature analysis provided by the embodiment of the present invention can execute the self-service terminal data synchronization optimization method based on feature analysis provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0063] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present invention.

[0064] The above specific embodiments do not constitute a limitation to the scope of protection of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of this application should be included in the scope of protection of this application. In some cases, the actions or steps recorded in this application can be performed in an order different from that in the embodiments and can still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A self-service terminal data synchronization optimization method based on feature analysis, characterized in that: include: Obtain the synchronization data port, data characteristics, and access records of the self-service terminal; Identifying data synchronization features based on the synchronization data port, data features, and access records; Analyze the relationship among the time synchronization dimension, the network transmission dimension, and the user access dimension according to the data synchronization characteristics to obtain the conflict relationship; Search for conflict relationships and abnormal synchronization information based on the data synchronization log of the self-service terminal to obtain conflict relationship record information and abnormal synchronization record information; Perform conditional probability calculation based on the conflict relationship record information and the abnormal synchronization record information, and output the abnormal probability of the conflict relationship; According to the abnormal probability of the conflict relationship, the synchronization strategy balance identification and optimization of each synchronization resource of the synchronization data port of the self-service terminal is performed, and the data synchronization strategy result is output. The synchronization control of the self-service terminal is performed based on the data synchronization strategy result.

2. The self-service terminal data synchronization optimization method based on feature analysis according to claim 1 is characterized in that: According to the data synchronization characteristics, the relationship between the time synchronization dimension, the network transmission dimension, and the user access dimension is analyzed to obtain the conflict relationship, including: Perform dimensional relationship alignment according to the time synchronization dimension, network transmission dimension, and user access dimension respectively; Extracting synchronization cross resources based on the alignment relationship, where the synchronization cross resources are resources commonly occupied by various types of synchronization data in the self-service terminal; Searching for conflict points based on the usage load status of the synchronization cross resource, wherein the conflict point is a synchronization usage node where the synchronization cross resource occupancy ratio exceeds a load threshold and the synchronization efficiency decreases; A mapping association is established between the conflict point, the relationship dimension, and the resource load ratio to obtain the conflict relationship.

3. The self-service terminal data synchronization optimization method based on feature analysis according to claim 2 is characterized in that: Dimensional relationship alignment is performed according to the time synchronization dimension, network transmission dimension, and user access dimension, including: Configuring key characteristic parameters of the time synchronization dimension, network transmission dimension, and user access dimension, wherein the key characteristic parameters include time window and synchronization frequency; Performing key feature identification and labeling on the data synchronization feature according to the key feature parameters; Align the corresponding dimensions based on key feature identifiers.

4. The self-service terminal data synchronization optimization method based on feature analysis according to claim 1, characterized in that: Performing conditional probability calculation based on the conflict relationship record information and the abnormal synchronization record information to output the abnormal probability of the conflict relationship includes: Calculating the probability of conflict occurrence based on the conflict relationship record information; Calculating a simultaneous occurrence probability based on the conflict relationship record information and the abnormal synchronization record information; According to the conflict occurrence probability and the simultaneous occurrence probability, the abnormal probability of the conflict relationship is calculated using a conditional probability formula.

5. The self-service terminal data synchronization optimization method based on feature analysis according to claim 1 is characterized in that: According to the abnormal probability of the conflict relationship, the synchronization strategy of each synchronization resource of the synchronization data port of the self-service terminal is balanced and optimized, and the data synchronization strategy result is output, including: According to the abnormal probability of the conflict relationship, configuring the conflict relationship balance weight; Based on the abnormal probability of the conflict relationship, obtaining a first conflict relationship strategy combination, a second conflict relationship strategy combination, and so on until the Nth conflict relationship strategy combination, where N is the number of conflict relationships; The first conflict relationship strategy combination, the second conflict relationship strategy combination, and up to the Nth conflict relationship strategy combination are balanced and identified according to the conflict relationship balance weight to obtain the data synchronization strategy result.

6. The self-service terminal data synchronization optimization method based on feature analysis according to claim 5, characterized in that: Based on the abnormal probability of the conflict relationship, obtaining a first conflict relationship strategy combination, a second conflict relationship strategy combination, and up to an Nth conflict relationship strategy combination, includes: Perform conflict relationship compensation analysis based on the conflict relationship to determine compensation direction and compensation parameters; According to the compensation direction and compensation parameters, the dimension parameters of the conflict relationship are searched and mutated to obtain a conflict relationship strategy combination.

7. The self-service terminal data synchronization optimization method based on feature analysis according to claim 6 is characterized in that: Performing balanced identification on the first conflict relationship strategy combination, the second conflict relationship strategy combination, and up to the Nth conflict relationship strategy combination according to the conflict relationship balance weight to obtain the data synchronization strategy result includes: Establish the cost function of each conflict relationship; Balancing the conflict relationship strategy combination based on a cost function of the conflict relationship; Establishing an evaluation function for the self-service terminal, and using the evaluation function to evaluate the strategy costs of the first conflict relationship strategy combination, the second conflict relationship strategy combination, and up to the Nth conflict relationship strategy combination; The strategy cost evaluation is minimized and searched based on the conflict relationship balance weight to obtain the data synchronization strategy result.

8. The self-service terminal data synchronization optimization system based on feature analysis is characterized by: The system is used to implement the self-service terminal data synchronization optimization method based on feature analysis according to any one of claims 1 to 7, and the system includes: Data record acquisition module, used to obtain the synchronization data port, data characteristics, and access records of the self-service terminal; A data synchronization feature identification module, configured to identify data synchronization features based on the synchronization data port, data features, and access records; A conflict relationship acquisition module is used to perform relationship analysis on the time synchronization dimension, the network transmission dimension, and the user access dimension according to the data synchronization characteristics to obtain the conflict relationship; An information search module is used to search for conflict relationships and abnormal synchronization information based on the data synchronization log of the self-service terminal, and obtain conflict relationship record information and abnormal synchronization record information; A conditional probability calculation module, configured to perform conditional probability calculation based on the conflict relationship record information and the abnormal synchronization record information, and output an abnormal probability of the conflict relationship; The synchronization strategy balance identification and optimization module is used to perform synchronization strategy balance identification and optimization of each synchronization resource of the synchronization data port of the self-service terminal according to the abnormal probability of the conflict relationship, output the data synchronization strategy result, and use the data synchronization strategy result to perform synchronization control of the self-service terminal.

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