Financial data scheduling visualization platform system

Abstract

The present invention discloses a financial data scheduling visualization platform system, which specifically relates to the technical field of financial data management. By acquiring multiple status information when a chart is updated, a jam coefficient is generated to prevent jam risks, and preventive judgment and processing are performed before the jam problem occurs to avoid negative impact on user experience. When jam risks occur, a secondary update time queue is constructed, the terminal load status is acquired to generate a performance value, the current load status is evaluated, and an intelligent judgment is made as to whether to perform a secondary update. Fuzzy logic is used to determine the best update time, optimize resource allocation, prevent negative impact on user experience, avoid unnecessary secondary updates, and reduce system resource waste.

Description

Technical Field

[0001] The present invention relates to the technical field of financial data management, and more specifically, to a financial data scheduling visualization platform system. Background Art

[0002] As the scale of enterprises expands and the business becomes more complex, the amount of data involved in financial management has exploded. The financial data scheduling visualization platform system is a financial data visualization platform that integrates data scheduling, visualization analysis, security protection, integration, scalability, and real-time monitoring. By introducing such a system, enterprises can manage and analyze financial data more efficiently, provide reliable support for decision-making, and promote the sustainable development of the business.

[0003] Existing financial data scheduling visualization platform systems usually display the collected and processed financial data in various ways such as charts, graphs and dashboards, and update the display forms of charts, graphs and dashboards in real time according to the real-time processed financial data. However, with the continuous growth of financial data and the frequent interaction of users, the load of the system will also increase, which may cause updates to be stuck. Since it is impossible to timely perceive and warn of possible update jams and humans cannot distinguish their updated status, the display of financial data does not match the actual situation. Decision makers may make decisions based on inaccurate or outdated information, which may lead to poor business results and affect the real-time display of financial data, reducing users' trust in the system.

[0004] In order to solve the above defects, a technical solution is now provided. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a financial data scheduling visualization platform system to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The financial data scheduling visualization platform system includes a data acquisition module, a model building module, and an update control module, and each module is connected through signals;

[0008] The data acquisition module is used to obtain multiple update status information when the financial data scheduling visualization platform system updates the chart, and transmit the multiple update status information to the model building module; it is also used to obtain multiple load status information of the terminal device, and transmit the multiple load status information to the model building module;

[0009] A model building module is used to build an update hidden danger monitoring model based on multiple update status information and generate a jamming coefficient; it is also used to build a terminal load monitoring model based on multiple load status information, generate a terminal load performance value, and transmit the jamming coefficient and the terminal load performance value to the update control module;

[0010] The update control module is used to determine the best time for the second update of the chart using fuzzy logic according to the jam coefficient and the terminal load performance value.

[0011] In a preferred embodiment, the multiple pieces of update status information include chart rendering information and user interaction information;

[0012] The chart rendering information includes the chart rendering time anomaly index, and the user interaction information includes the user interaction frequency. The chart rendering time anomaly index and the user interaction frequency are marked as .

[0013] In a preferred embodiment, the logic for obtaining the chart rendering time anomaly index is as follows:

[0014] Get the actual rendering time of the chart , i represents the order number of different types of charts, i={1,2,...,n}, n represents a positive integer; according to the rendering time Calculate the chart rendering time anomaly index, the expression is as follows , Indicates the standard rendering time for different types of charts.

[0015] The calculation expression of user interaction frequency is as follows ,in Represents the total number of times users interact with the chart over a period of time. Indicates a preset time period.

[0016] In a preferred embodiment, the multiple load status information of the terminal device includes various load indicators of the display terminal, including CPU usage, memory share, disk usage, and network bandwidth utilization, which are obtained and passed to the model building module.

[0017] In a preferred embodiment, the jam coefficient is calculated by weighted summation based on the chart rendering time anomaly index and the user interaction frequency;

[0018] Compare the jamming coefficient with a preset jamming coefficient threshold;

[0019] If the jam coefficient is greater than or equal to the jam coefficient threshold, the current time point is recorded, and a secondary update time queue is constructed according to the recorded time point;

[0020] If the jamming coefficient is less than the jamming coefficient threshold, there is no need to perform a second update on the chart data updated at the current time.

[0021] In a preferred embodiment, the terminal load performance value is calculated by weighted summation according to the CPU usage rate, memory usage rate, disk usage rate, and network bandwidth utilization rate;

[0022] comparing the terminal load performance value with a preset terminal load performance value threshold;

[0023] If the terminal load performance value is greater than or equal to the terminal load performance value threshold, the load condition cannot be satisfied to perform a secondary update of the chart of the financial data with a potential jamming risk in the secondary update time queue, and the evaluation is continued;

[0024] If the terminal load performance value is less than the terminal load performance value threshold, the load condition is sufficient to perform a secondary update on the chart of the financial data that has a potential risk of jamming in the secondary update time queue.

[0025] In a preferred embodiment, the update control module uses fuzzy logic to determine the best time for the secondary update of the chart according to the jamming coefficient and the terminal load performance value. The specific steps are as follows:

[0026] After receiving the jamming coefficient and the terminal load performance value, the update control module defines the jamming coefficient and the terminal load performance value as input variables and divides them into different fuzzy sets respectively;

[0027] The optimal moment for the second update of the graph is defined as the output variable, which is divided into fuzzy sets;

[0028] Formulate a set of fuzzy rules to describe the influence of the input variables of the jam coefficient and the terminal load performance value on the output variable of the best time for the second update of the chart;

[0029] Fuzzy reasoning is performed based on fuzzy rules to determine the best time for the chart to be updated twice.

[0030] Technical effects and advantages of the present invention:

[0031] 1. The present invention obtains multiple update status information during the update and generates a jamming coefficient when the financial data scheduling visualization platform system updates the chart, which is used to identify the authenticity of each chart update rendering, determine whether there is a hidden danger of jamming, and make preventive judgments and processing before the jamming problem occurs to avoid negative impact on user experience. When there is a hidden danger of jamming, a secondary update time queue is constructed, and multiple load status information of the terminal display device is obtained to generate a terminal load performance value. The load status of the display terminal at the current moment is monitored and evaluated to determine whether the financial data with hidden dangers of jamming in the secondary update time queue can be updated for the second time at the current moment. According to the jamming coefficient and the terminal load performance value, fuzzy logic is used to determine the best time for the secondary update, and the timing of the secondary update is optimized. By dynamically judging the jamming situation and load status of the chart update, the system can allocate resources more intelligently, avoid unnecessary secondary updates, and reduce waste of system resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0033] Figure 1 Schematic diagram of the structure of the system of the embodiment of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] The present invention provides Figure 1 The financial data scheduling visualization platform system shown includes a data acquisition module, a model building module, and an update control module, and each module is connected through signals;

[0036] The data acquisition module is used to obtain multiple update status information when the financial data scheduling visualization platform system updates the chart, and transmit the multiple update status information to the model building module; it is also used to obtain multiple load status information of the terminal device, and transmit the multiple load status information to the model building module;

[0037] The multiple pieces of update status information include chart rendering information and user interaction information;

[0038] The chart rendering information includes the chart rendering time anomaly index, and the user interaction information includes the user interaction frequency. The chart rendering time anomaly index and the user interaction frequency are marked as ;

[0039] When the financial data scheduling visualization platform system is updating the chart, it will re-render the relevant charts of the visualization interface according to the processed financial data to ensure that the processed financial data can be converted into charts in time for users to view. The chart rendering time abnormality index is used to measure the degree of abnormality in the rendering time of the chart when the financial data scheduling visualization platform system is updating the chart. The higher the chart rendering time abnormality index, the more likely the chart update may be a stuck behavior. If it is an update stuck, it may cause the next update response. Because the rendering task is not completed in this update, the system may directly enter the next chart rendering, resulting in the failure of this chart update. The display is inconsistent with the actual situation. When the rendering time of the chart is abnormal, the potential stuck risk is higher.

[0040] The logic for obtaining the chart rendering time anomaly index is as follows:

[0041] Get the actual rendering time of the chart , i represents the order number of different types of charts, i={1,2,...,n}, n represents a positive integer; according to the rendering time Calculate the chart rendering time anomaly index, the expression is as follows , Indicates the standard rendering time for different types of charts.

[0042] User interaction frequency refers to the real-time interaction between the user and the chart, such as zooming, dragging, refreshing and other interactive operations. These real-time response interactions will also cause the chart to be re-rendered. When the rendering response triggered by the user interaction overlaps with the rendering response caused by data update, it may cause abnormal lag. The higher the user interaction frequency, the higher the potential lag risk.

[0043] The calculation expression of user interaction frequency is as follows ,in Represents the total number of times users interact with the chart over a period of time. Indicates a preset time period;

[0044] After the data acquisition module obtains the chart rendering time anomaly index and the user interaction frequency, the chart rendering time anomaly index and the user interaction frequency are sent to the model construction module;

[0045] The multiple load status information of the terminal device includes various load indicators of the display terminal, including CPU usage, memory usage, disk usage, and network bandwidth utilization, which are obtained and passed to the model building module;

[0046] The load indicators of the display terminal are used to measure the current system load status of various display terminal devices for chart display. If the current system load of the display terminal device is higher, the accuracy of the secondary update of the chart will be lower, that is, the current time point is not the best time to perform the secondary update of the chart;

[0047] It should be noted that the load indicators of the display terminal can be obtained in real time by using professional performance monitoring tools such as top, Prometheus, Grafana, etc., and selecting the appropriate API interface to transmit the data of the performance monitoring tool to the financial data scheduling visualization platform system;

[0048] A model building module is used to build an update hidden danger monitoring model based on multiple update status information and generate a jamming coefficient; it is also used to build a terminal load monitoring model based on multiple load status information, generate a terminal load performance value, and transmit the jamming coefficient and the terminal load performance value to the update control module;

[0049] According to the chart rendering time anomaly index and user interaction frequency, an update hidden danger monitoring model is built to generate a jamming coefficient. The authenticity of each chart update rendering is identified to determine whether there is a jamming hidden danger. According to the update hidden danger monitoring model, the formula for generating the jamming coefficient is as follows ,in represents the stutter coefficient, They are the chart rendering time anomaly index and the weight factor of user interaction frequency. The specific values ​​can be set according to the actual situation.

[0050] From the above calculation formula, it can be seen that the greater the chart rendering time abnormality index and the user interaction frequency, the greater the jam coefficient, the higher the probability of jamming hidden dangers, and the chart data updated at the current time needs to be updated twice; conversely, the smaller the chart rendering time abnormality index and the user interaction frequency, the smaller the jam coefficient, the lower the probability of jamming hidden dangers, and the lower the probability of needing to update the chart data updated at the current time twice;

[0051] Compare the jam coefficient with the preset jam coefficient threshold to identify the authenticity of each chart update rendering and determine whether there is a jam risk;

[0052] If the jam coefficient is greater than or equal to the jam coefficient threshold, it indicates that the authenticity of the chart update rendering is lower and there is a jam risk. The chart data updated at the current time needs to be updated again. The current time point is recorded and a secondary update time queue is constructed based on the recorded time point. The queue is arranged in chronological order and there is financial data that needs to be updated at the corresponding time point in the queue.

[0053] If the jam coefficient is less than the jam coefficient threshold, it indicates that the authenticity of the chart update rendering is very high, there is no jam risk, and there is no need to update the chart data updated at the current time again;

[0054] A terminal load monitoring model is constructed based on CPU usage, memory usage, disk usage, and network bandwidth utilization to generate a terminal load performance value. The load status of the display terminal at the current moment is monitored and evaluated to determine whether the financial data with hidden dangers of jamming in the secondary update time queue can be updated for the second time. The formula for generating the terminal load performance value based on the terminal load monitoring model is as follows ,in Indicates the terminal load performance value, Indicates CPU usage. Indicates the memory usage ratio. Indicates disk usage. Indicates the network bandwidth utilization. They represent the weight factors of CPU usage, memory usage, disk usage, and network bandwidth utilization respectively. The specific values ​​can be set according to the actual situation.

[0055] It should be noted that the start time of monitoring and evaluating the load status of the display terminal is consistent with the construction time of the secondary update time queue;

[0056] It can be seen from the above calculation formula that the greater the CPU usage rate, memory share, disk usage rate, and network bandwidth utilization rate, the greater the terminal load performance value, which indicates that the load state of the display terminal at the current moment is greater. If the financial data with potential jamming risks in the secondary update time queue is updated for the second time at the current moment, there may still be potential jamming risks, and it is not the best time for the second update; on the contrary, the smaller the CPU usage rate, memory share, disk usage rate, and network bandwidth utilization rate, the smaller the terminal load performance value, which indicates that the load state of the display terminal at the current moment is smaller, and it can be updated for the second time;

[0057] Compare the terminal load performance value with the preset terminal load performance value threshold, monitor and evaluate the load status of the display terminal at the current moment, and determine whether the chart of the financial data with potential jamming risks in the secondary update time queue can be updated at the current moment;

[0058] If the terminal load performance value is greater than or equal to the terminal load performance value threshold, it indicates that the load state of the terminal displayed at the current moment is greater, and its load condition cannot meet the secondary update of the chart of the financial data with potential jamming risks in the secondary update time queue, and continuous evaluation is performed;

[0059] If the terminal load performance value is less than the terminal load performance value threshold, it indicates that the load state of the display terminal at the current moment is smaller, and its load condition can meet the secondary update of the chart of the financial data with potential jamming risks in the secondary update time queue;

[0060] An update control module is used to determine the best time for the second update of the chart using fuzzy logic according to the jam coefficient and the terminal load performance value;

[0061] The working process of the update control module is as follows:

[0062] After receiving the jamming coefficient and the terminal load performance value, the update control module defines the jamming coefficient and the terminal load performance value as input variables and divides them into different fuzzy sets respectively.

[0063] For example, "A1", "A2" are for the jamming coefficient, and "B1", "B2" are for the terminal load performance value.

[0064] The "A1" and "A2" described above correspond to the fuzzy definition of the stutter coefficient, that is, if the stutter coefficient is greater than or equal to the stutter coefficient threshold, the fuzzy definition of the stutter coefficient is "A1"; if the stutter coefficient is less than the stutter coefficient threshold, the fuzzy definition of the stutter coefficient is "A2";

[0065] The "B1" and "B2" described above correspond to the fuzzy definition of the terminal load performance value, that is, if the terminal load performance value is greater than or equal to the terminal load performance value threshold, the fuzzy definition of the terminal load performance value is "B1"; if the terminal load performance value is less than the terminal load performance value threshold, the fuzzy definition of the terminal load performance value is "B2";

[0066] The optimal moment for the secondary update of the graph is defined as the output variable, which is divided into fuzzy sets, e.g., "C1", "C2" for the optimal moment.

[0067] The "C1" and "C2" described above correspond to the fuzzy definition of the best time for the chart to be updated twice, that is, if the chart can be updated twice at the current moment, the fuzzy definition of the best time for the chart to be updated twice is "C1"; if the chart cannot be updated twice at the current moment, the fuzzy definition of the best time for the chart to be updated twice is "C2";

[0068] Formulate a set of fuzzy rules to describe the impact of different input variables on output variables. The definition of rules can be based on professional knowledge or obtained through data analysis and experiments. For example:

[0069] The jam coefficient is marked as K, the terminal load performance value is marked as F, and the best time for the second update of the chart is marked as T.

[0070] Rule 1: IF (K is A1) AND (F is B1) THEN (T is C2)

[0071] Rule 2: IF (K is A1) AND (F is B2) THEN (T is C1) ...

[0073] Fuzzy reasoning is performed based on fuzzy rules to determine the best time for the chart to be updated twice.

[0074] The present invention obtains multiple update status information during the update and generates a jam coefficient when the financial data scheduling visualization platform system updates the chart, which is used to identify the authenticity of each chart update rendering, determine whether there is a jam risk, and make preventive judgments and processing before the jam problem occurs to avoid negative impact on user experience. When there is a jam risk, a secondary update time queue is constructed, and multiple load status information of the terminal display device is obtained to generate a terminal load performance value. The load status of the display terminal at the current moment is monitored and evaluated to determine whether the financial data with jam risks in the secondary update time queue can be updated for the second time at the current moment. According to the jam coefficient and the terminal load performance value, fuzzy logic is used to determine the best time for the secondary update, and the timing of the secondary update is optimized. By dynamically judging the jam situation and load status of the chart update, the system can allocate resources more intelligently, avoid unnecessary secondary updates, and reduce the waste of system resources.

[0075] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0076] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0077] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0078] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0079] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0080] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0081] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. Financial data scheduling visualization platform system, characterized by: It includes a data acquisition module, a model building module, and an update control module, and each module is connected through signals; The data acquisition module is used to obtain multiple update status information when the financial data scheduling visualization platform system updates the chart, and transmit the multiple update status information to the model building module; it is also used to obtain multiple load status information of the terminal device, and transmit the multiple load status information to the model building module; The multiple pieces of update status information include chart rendering information and user interaction information; The chart rendering information includes the chart rendering time anomaly index, and the user interaction information includes the user interaction frequency. The chart rendering time anomaly index and the user interaction frequency are marked as ; The logic for obtaining the chart rendering time anomaly index is as follows: Get the actual rendering time of the chart , i represents the order number of different types of charts, i={1,2,...,n}, n represents a positive integer; according to the rendering time Calculate the chart rendering time anomaly index, the expression is as follows , Indicates the standard rendering time for different types of charts. The calculation expression of user interaction frequency is as follows ,in Represents the total number of times users interact with the chart over a period of time. Indicates a preset time period; A model building module is used to build an update hidden danger monitoring model based on multiple update status information and generate a jamming coefficient; it is also used to build a terminal load monitoring model based on multiple load status information, generate a terminal load performance value, and transmit the jamming coefficient and the terminal load performance value to the update control module; The multiple load status information of the terminal device includes various load indicators of the display terminal, including CPU usage, memory usage, disk usage, and network bandwidth utilization, which are obtained and passed to the model building module; The jam coefficient is calculated by weighted summation based on the chart rendering time anomaly index and user interaction frequency: The terminal load performance value is calculated by weighted summation based on CPU usage, memory usage, disk usage, and network bandwidth utilization; An update control module is used to determine the best time for the second update of the chart using fuzzy logic according to the jam coefficient and the terminal load performance value; According to the jam coefficient and the terminal load performance value, the specific steps of using fuzzy logic to determine the best time for the second update of the chart are as follows: After receiving the jamming coefficient and the terminal load performance value, the update control module defines the jamming coefficient and the terminal load performance value as input variables and divides them into different fuzzy sets respectively; The optimal moment for the second update of the graph is defined as the output variable, which is divided into fuzzy sets; Formulate a set of fuzzy rules to describe the influence of the input variables of the jam coefficient and the terminal load performance value on the output variable of the best time for the second update of the chart; Fuzzy reasoning is performed based on fuzzy rules to determine the best time for the chart to be updated twice.

2. The financial data scheduling visualization platform system according to claim 1 is characterized by: Compare the jamming coefficient with a preset jamming coefficient threshold; If the jam coefficient is greater than or equal to the jam coefficient threshold, the current time point is recorded, and a secondary update time queue is constructed according to the recorded time point; If the jamming coefficient is less than the jamming coefficient threshold, there is no need to perform a second update on the chart data updated at the current time.

3. The financial data scheduling visualization platform system according to claim 1 is characterized by: comparing the terminal load performance value with a preset terminal load performance value threshold; If the terminal load performance value is greater than or equal to the terminal load performance value threshold, the load condition cannot be satisfied to perform a secondary update of the chart of the financial data with a potential jamming risk in the secondary update time queue, and the evaluation is continued; If the terminal load performance value is less than the terminal load performance value threshold, the load condition is sufficient to perform a secondary update on the chart of the financial data that has a potential risk of jamming in the secondary update time queue.

Images