Budget control method and system
By pre-processing and abnormal detection of travel expense data, the problem of inaccurate identification of abnormal data for travel expenses in the prior art is solved, the accuracy and authenticity of travel expenses are improved, and the economic losses of the company are reduced.
Patent Information
- Application Number
- CN202411764559.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-04
- Publication Date
- 2025-03-28
AI Technical Summary
It is difficult for the prior art to accurately identify and control abnormal data in travel expenses, resulting in unreasonable situations in the company's expenditure and reimbursement of travel expenses, resulting in losses.
By collecting initial travel expense data and traveler data, pre-processing is performed to remove duplication, missing and outliers, a budget expense database is established, and an abnormal expense data is identified through historical data analysis, marked and reimbursement confirmation.
It improves the accuracy of identification and analysis of travel expenses, ensures the authenticity and rationality of travel expenses, and reduces the company's economic losses.
Smart Images
Figure CN119719082A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of image processing technology, and in particular to a budget control method and system. Background Art
[0002] Budget control is one of the important tasks in managing and controlling expense expenditure, and among them, travel expense budget control is more important. Due to the differences in consumption levels, salary levels, etc. in various cities, travel expenses must be different for different cities. If you go to fourth- and fifth-tier cities and give them the same travel expenses as first-tier cities, the company's expenses will increase. If you go to first-tier cities and give them the same travel expenses as fourth- and fifth-tier cities, employees will inevitably object. Therefore, if unreasonable travel expenses appear, such as over-reimbursement of travel expenses, it will inevitably cause losses to the company. Summary of the invention
[0003] The embodiments of the present application provide a budget control method and system, which can improve the accuracy of identifying abnormal data in the prior art.
[0004] The budget control method provided in this application includes the following steps: Step 1: Collect expense data and collect initial travel expense data a1; Step 2: First preprocessing, performing first preprocessing on the initial travel expense data a1 collected in step 1 to obtain processed data a2; Step 3: Collect personnel data, collect initial business trip personnel data a3; Step 4: Second preprocessing, performing second preprocessing on the initial business traveler data a3 collected in step 3 to obtain processed data a4; Step 5: Database establishment, import the pre-processed data a2 and a4 into the database, and process them to obtain the budget cost database data a5; Step 6: Historical data collection, collect historical travel expense data and obtain a6 after processing; Step 7: Abnormal expense detection, analyzing and comparing the historical travel expense data a6 with the database data a5, identifying abnormal expense data, and marking them to obtain marked data a7; Step 8: Output the results and confirm the budget reimbursement.
[0005] Before collecting the travel expenses a1, it also includes: data b1 collected after dividing each city, and the data b1 includes transportation cost data c1, catering data c2, accommodation data c3 and communication data c4.
[0006] Before collecting the business trip personnel data a3, it also includes: collecting the rank status data of all personnel to obtain data b2, which includes position level data d1, age level data d2, gender data d3, length of service data d4 and business trip frequency data d5.
[0007] The first preprocessing is data cleaning, which involves cleaning and organizing the collected data a1, including removing duplicate data, processing missing values and outliers, etc., to ensure the accuracy and completeness of the data, which is data a2.
[0008] Cleaning the data includes: Handle missing values, check if there are missing values in the data, and use interpolation methods to fill in missing values; Handling duplicate values: Detect and handle duplicate values in data, using unique identifiers to remove duplicates; Dealing with outliers: Identifying and dealing with outliers in data, using the method of adding or subtracting several times the standard deviation of the mean to identify and deal with outliers; The abnormal value processing may also include outlier processing: for abnormal values that are obviously deviated from the normal range, they may be replaced with reasonable values.
[0009] In a second aspect, the budget control method processing system provided by the present application includes: The expense data collection module is used to collect initial travel expense data a1; A first preprocessing module performs a first preprocessing on the collected initial travel expense data a1 to obtain processed data a2; The personnel data collection module collects the initial business trip personnel data a3; A second preprocessing module performs a second preprocessing on the collected initial business traveler data a3 to obtain processed data a4; The database establishment module imports the pre-processed data a2 and a4 into the database and processes them to obtain the budget cost database data a5; Historical data collection module, historical data collection, collects historical travel expense data and obtains a6 after processing; Abnormal expense detection: analyze and compare the historical travel expense data a6 with the database data a5, identify abnormal expense data, and mark them to obtain marked data a7; Output result module to confirm budget reimbursement.
[0010] In a third aspect, the electronic device provided in the present application includes a memory and a processor, wherein the memory stores a computer program, and the processor is used to run the computer program in the memory to implement the steps in the budget control method provided in the present application.
[0011] In a fourth aspect, the computer-readable storage medium provided in the present application stores a plurality of instructions, which are suitable for loading by a processor to implement the steps in the budget control method provided in the present application.
[0012] In a fifth aspect, the computer program product provided in the present application includes a computer program or instructions, which, when executed by a processor, implement the steps in the budget control method provided in the present application.
[0013] In the present application, compared with the related art, step 1: collecting expense data, collecting initial travel expense data a1, step 2: first preprocessing, performing first preprocessing on the initial travel expense data a1 collected in step 1, and obtaining processed data a2; step 3: collecting personnel data, collecting initial business trip personnel data a3; step 4: second preprocessing, performing second preprocessing on the initial business trip personnel data a3 collected in step 3, and obtaining processed data a4; step 5: database establishment, importing the preprocessed data a2 and a4 into the database, and processing them to obtain the budget expense data a2 and a4. Use database data a5; Step 6: Historical data collection, collect historical travel expense data, and obtain a6 after processing; Step 7: Abnormal expense detection, analyze and compare the historical travel expense data a6 with the database data a5, identify abnormal expense data, and mark it to obtain marked data a7; Step 8: Output the results and confirm the budget reimbursement. Through the above steps, an effective budget control calculation model can be established to identify and analyze the travel expense characteristics of business travelers and detect abnormal data, greatly improving the accuracy and authenticity of travel expenses. BRIEF DESCRIPTION OF THE DRAWINGS
[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.
[0015] Figure 1 is a schematic diagram of a scenario of a budget control system provided by an embodiment of the present application; Figure 2 It is a flowchart of an embodiment of the budget control method provided by the embodiment of the present application; Figure 3 This is a schematic diagram of city data collection in an embodiment of the budget control method provided in the embodiment of the present application; Figure 4 This is a schematic diagram of personnel rank status in an embodiment of the budget control method provided in the embodiment of the present application; Figure 5A schematic diagram of the structure of the budget control system provided in the embodiment of the present application Figure 6 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0016] It should be noted that the principles of the present application are illustrated by implementing them in an appropriate computing environment. The following description is based on the illustrated specific embodiments of the present application and should not be considered as limiting other specific embodiments of the present application that are not described in detail herein.
[0017] In the following description of the present application, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it can 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.
[0018] In the following description of the present application, the terms "first\second\third" involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged with a specific order or sequence where permitted, so that the embodiments of the present application described here can be implemented in an order other than that illustrated or described here.
[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.
[0020] In order to improve the effect of image processing of gait based on image recognition, the embodiments of the present application provide a gait method based on image recognition, a gait system based on image recognition, an electronic device, a computer-readable storage medium, and a computer program product. The gait method based on image recognition can be executed by a gait system based on image recognition, or by an electronic device integrated with the gait processing system based on image recognition.
[0021] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.
[0022] Please refer to Figure 1 , the present application also provides a budget control method system, such as Figure 1As shown, the budget control method system includes an electronic device 100, and the processing system of the budget control method provided by the present application is integrated in the electronic device 100.
[0023] Among them, the electronic device 100 can be any device equipped with a processor and has processing capabilities, such as mobile electronic devices with processors such as smart phones, tablet computers, PDAs, laptops, smart speakers, or fixed electronic devices with processors such as desktop computers, televisions, servers, industrial equipment, etc.
[0024] In addition, if Figure 1 As shown, the budget control method system may further include a memory 200 for storing original data, intermediate data and result data.
[0025] In the embodiment of the present application, the memory 200 may be a cloud storage. Cloud storage is a new concept extended and developed from the concept of cloud computing. A distributed cloud storage system (hereinafter referred to as the storage system) refers to a storage system that uses cluster applications, grid technology, and distributed storage file systems and other functions to bring together a large number of storage devices of various types (storage devices are also called storage nodes) in the network through application software or application interfaces to work together and jointly provide data storage and business access functions to the outside world.
[0026] At present, the storage method of the storage system is: create a logical volume, and when creating a logical volume, allocate physical storage space for each logical volume, and the physical storage space may be composed of disks of a storage device or several storage devices. The client stores data on a logical volume, that is, stores the data on the file system. The file system divides the data into many parts, each of which is an object. The object contains not only data but also additional information such as data identification (ID, ID entity). The file system writes each object into the physical storage space of the logical volume, and the file system records the storage location information of each object, so that when the client requests to access the data, the file system can allow the client to access the data according to the storage location information of each object.
[0027] The process of the storage system allocating physical storage space to a logical volume is as follows: based on the estimated capacity of the objects stored in the logical volume (this estimate often has a large margin relative to the actual capacity of the objects to be stored) and the grouping of independent redundant disk arrays (RAID, Redundant Array of Independent Disks), the physical storage space is divided into stripes in advance. A logical volume can be understood as a stripe, thereby allocating physical storage space to the logical volume.
[0028] It should be noted that Figure 1 The scenario diagram of the budget control method system shown is only an example. The gait image processing system and scenario described in the embodiment of the present application are intended to more clearly illustrate the technical solution of the embodiment of the present application, and do not constitute a limitation on the technical solution provided in the embodiment of the present application. A person of ordinary skill in the art can know that with the evolution of the gait image processing system and the emergence of new business scenarios, the technical solution provided in the embodiment of the present application is also applicable to similar technical problems.
[0029] It should be noted that the serial numbers of the following embodiments are not intended to limit the preferred order of the embodiments.
[0030] Please refer to Figure 2 , Figure 2 FIG. 1 is a flow chart of an embodiment of the budget control method provided in the embodiment of the present application. Figure 2 As shown, the process of the budget control method provided by this application is as follows: S101: Step 1: Collect expense data, collect initial travel expense data a1; It is understandable that the pre-settings require the collection of basic values for travel expenses, which include real-time reimbursement data at the business trip destination and consumption at the destination in the past three years, including transportation costs, accommodation costs, and food and beverage expenses.
[0031] S102: Step 2: First preprocessing, performing first preprocessing on the initial travel expense data a1 collected in step 1 to obtain processed data a2; The collected data a1 is raw data that has not been processed and must be preprocessed before it can be used for budget control.
[0032] S103: Step 3: Collect personnel data, collect initial business trip personnel data a3; The company's personnel are divided into different positions and ranks, and the information is collected as to whether they are accompanied by anyone. If so, it is determined whether they are employees of the company. If not, they will be eliminated.
[0033] S104: Step 4: Second preprocessing, performing second preprocessing on the initial business traveler data a3 collected in step 3 to obtain processed data a4; The pre-processing method for the business traveler data a3 is to calculate the average cost: calculate the average travel cost based on the business travelers of different job levels and positions; Compare expense differences: Compare travel expenses for different job levels and analyze the reasons for expense differences. There may be some differences between job levels, such as senior management's travel expenses are usually higher. By comparing expense differences, potential optimization opportunities or needs can be discovered.
[0034] S105: Step 5: Database establishment, importing the pre-processed data a2 and a4 into the database and processing them to obtain the budget cost database data a5; S106: Step 6: Historical data collection, collecting historical travel expense data and processing to obtain a6; The method of collecting historical data is to collect travel expense reimbursement records within the past 12 months, including detailed information such as the name of the business traveler, date of business trip, destination, transportation expenses, accommodation expenses, and food expenses, and to Time trend analysis: By grouping and summarizing expense reimbursement record data by time and analyzing the time trend of travel expenses, you can observe the changes in expenses in different time periods and identify seasonal or cyclical trends.
[0035] Position and rank analysis: Associate expense reimbursement record data with the position and rank of business travelers to analyze expense differences between different positions and ranks. Compare expense levels of different positions and ranks to identify potential optimization opportunities or needs.
[0036] Regional analysis: Perform regional analysis based on the destination information in the expense reimbursement record data. By comparing the cost levels of different destinations, you can understand the differences in travel expenses in different regions and provide a reference for budget planning and decision-making.
[0037] S107: Step 7: abnormal expense detection, analyzing and comparing the historical travel expense data a6 with the database data a5, identifying abnormal expense data, and marking them to obtain marked data a7; S108: Step 8: Output the results and confirm the budget reimbursement.
[0038] It is understandable that after processing the abnormal data, a budget control direction that is in line with the interests of the company and business travelers is obtained, so that subsequent reimbursement can be processed.
[0039] Before collecting the travel expenses a1, it also includes: data b1 collected after dividing each city, and the data b1 includes transportation cost data c1, catering data c2, accommodation data c3 and communication data c4.
[0040] The division of cities needs to refer to factors such as administrative divisions, economic characteristics, and functional divisions; It is divided according to functions, such as commercial areas, residential areas, industrial areas, educational areas, cultural areas, etc. This division is based on the main functions and uses of different areas in the city, and the consumption situation in different areas varies greatly. For example, catering consumption in industrial areas is far lower than that in commercial areas. Therefore, after business trips to different cities, data analysis should also be conducted on the final destination area to give business travelers the fairest treatment.
[0041] Before collecting the business trip personnel data a3, it also includes: collecting the rank status data of all personnel to obtain data b2, which includes position level data d1, age level data d2, gender data d3, length of service data d4 and business trip frequency data d5.
[0042] It is important to note that business travelers are divided into male and female groups based on gender. This helps to understand the differences between different genders in business travel, such as business travel preferences, cost expenditures, and the degree of concern about safety issues.
[0043] Moreover, the job grade information of all the employees in the company is collected, regardless of whether they are likely to travel on business or not.
[0044] Divide business travelers into different groups based on their length of service (e.g., years with the company). This can help analyze the differences in business travel between experienced and new employees.
[0045] Business travelers are divided into high-frequency travelers and low-frequency travelers according to their travel frequency (e.g. monthly, quarterly, annually, etc.). This helps to understand the travel needs, budget planning, and efficiency optimization opportunities of different travel frequency groups. For example, when buying air tickets, choose more cost-effective packages, monthly tickets, etc., or rent a house in the destination city, which is more cost-effective. This more accurate data collection can make budget control more accurate.
[0046] Numerical features are a general term for variables in the collected data, such as business trip frequency, city name, consumption level, position, age, gender, etc. The data values generated by these features are collectively called numerical features.
[0047] The first preprocessing is data cleaning, which involves cleaning and organizing the collected data a1, including removing duplicate data, missing values, and outliers in the data a1, to ensure the accuracy and completeness of the data a1. After processing the data a1, accurate data a2 is obtained.
[0048] Data cleaning, including: To handle missing values, first check whether there are missing values in data a1, and use interpolation methods to fill in the missing values in data a1; specifically, use mean interpolation, as follows: First, calculate the mean of data a1: For numeric features, calculate the mean of the non-missing values of the feature, calculate the sum of all non-missing values, and divide the sum of all non-missing values by the number of non-missing values to get the missing value.
[0049] For example: To fill missing data of accommodation fee x and meal fee y on a monthly basis, calculate the mean value of accommodation fee x and meal fee y for all persons in value a1 this month (30 days) (with missing data), then calculate the mean value of accommodation fee x and meal fee y for each person in a single month (with missing data), then calculate the sum of non-missing values of accommodation fee x and meal fee y for all persons, divide the sum of non-missing values of accommodation fee x and meal fee y for all persons by the number of non-missing values, and finally get the mean value of non-missing values of accommodation fee x and meal fee y, which is used to fill missing data.
[0050] Fill missing values: For missing values, fill them with the mean of the non-missing values calculated above, and assign the mean of the non-missing values to the samples where the missing values are located.
[0051] Process duplicate values: detect and process duplicate values in data a1, mark non-duplicate values based on unique identifiers, delete unmarked duplicate values, and complete deduplication. The records are hashed using a hash function and the hash values are compared to determine if there are duplicate values.
[0052] Dealing with outliers: Identifying and dealing with outliers in data, using the method of adding or subtracting several times the standard deviation of the mean to identify and deal with outliers; First, identify the outliers in data a1, specifically: determine whether each data in data a1 exceeds the threshold range, and if so, mark the data exceeding the threshold range as an outlier; The threshold range can be determined by calculating the standard deviation, For example: Calculate the mean and standard deviation: For a given numerical feature, first calculate the mean and standard deviation of the feature. The mean represents the center position of the data, and the standard deviation represents the degree of dispersion of the data.
[0053] Define the threshold range: The product of the standard deviation and the preset multiple is used as the threshold range. Data outside the threshold range will be considered as outliers.
[0054] Identify outliers: Check if the data a1 is outside the range of the mean plus or minus multiples of the standard deviation. If so, mark it as an outlier.
[0055] Outlier processing can also be used to deal with outliers: for outliers that deviate significantly from the normal range, you can choose to replace them with reasonable values.
[0056] This processing method can make the data more accurate.
[0057] In order to better implement the gait method based on image recognition provided in the embodiment of the present application, the embodiment of the present application also provides a budget control system based on the above budget control method. The meanings of the terms are the same as those in the above budget control method. For specific implementation details, please refer to the description in the above method embodiment.
[0058] Please refer to Figure 5 , Figure 5 A schematic diagram of the structure of a budget control system provided in an embodiment of the present application, the budget control system may include: The expense data collection module is used to collect initial travel expense data a1; A first preprocessing module performs a first preprocessing on the collected initial travel expense data a1 to obtain processed data a2; The personnel data collection module collects the initial business trip personnel data a3; collects the business trip data of each person within a unit of time. The business trip data is based on the electronic records applied for from the company, which are collected separately and summarized overall.
[0059] A second preprocessing module performs a second preprocessing on the collected initial business traveler data a3 to obtain processed data a4; The database establishment module imports the pre-processed data a2 and a4 into the database and processes them to obtain the budget cost database data a5; Historical data collection module, historical data collection, collects historical travel expense data and obtains a6 after processing; Abnormal expense detection: analyze and compare the historical travel expense data a6 with the database data a5, identify abnormal expense data, and mark them to obtain marked data a7; Output result module to confirm budget reimbursement.
[0060] The specific implementation of each of the above modules can be found in the previous embodiments and will not be described in detail here.
[0061] An embodiment of the present application also provides an electronic device, including a memory and a processor, wherein the processor is used to execute the steps of the image recognition-based gait method provided in this embodiment by calling a computer program stored in the memory.
[0062] Please refer to Figure 6 , Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.
[0063] The electronic device may include components such as a processor 301 with one or more processing cores, a memory 302 with one or more computer-readable storage media, a power supply 303, and an input unit 304. Those skilled in the art will appreciate that the electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. Among them: The processor 301 is the control center of the electronic device, which uses various interfaces and lines to connect various parts of the entire electronic device, and executes various functions of the electronic device and processes data by running or executing software programs and / or modules stored in the memory 302, and calling data stored in the memory 302. Optionally, the processor 301 may include one or more processing cores; optionally, the processor 301 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 301.
[0064] The memory 302 can be used to store software programs and modules. The processor 301 executes various functional applications and data processing by running the software programs and modules stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 302 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.
[0065] The electronic device also includes a power supply 303 for supplying power to each component. Optionally, the power supply 303 can be logically connected to the processor 301 through a power management system, so as to manage charging, discharging, and power consumption through the power management system. The power supply 303 can also include any components such as one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, and power status indicators.
[0066] The electronic device may further include an input unit 304, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.
[0067] Although not shown, the electronic device may also include a display unit, an image acquisition component, etc., which will not be described in detail here. Specifically in this embodiment, the processor 301 in the electronic device will load the executable code corresponding to one or more computer programs into the memory 302 according to the following instructions, and the processor 301 will execute the steps in the gait method based on image recognition provided by the present application, such as: When the collection starts, collect expense data and collect initial travel expense data a1; first preprocess, perform first preprocessing on the initial travel expense data a1 collected in step 1 to obtain processed data a2; collect personnel data and collect initial business trip personnel data a3; second preprocessing, perform second preprocessing on the initial business trip personnel data a3 collected in step 3 to obtain processed data a4; database establishment, import the preprocessed data a2 and a4 into the database, and process them to obtain budget expense database data a5; historical data collection, collect historical travel expense data, and obtain a6 after processing; abnormal expense detection, analyze and compare the historical travel expense data a6 with the database data a5, identify abnormal expense data, and mark them to obtain marked data a7; output the results and confirm the budget reimbursement.
[0068] It should be noted that the electronic device provided in the embodiment of the present application and the budget control method in the above embodiment belong to the same concept, and its specific implementation process is detailed in the above related embodiments and will not be repeated here.
[0069] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program stored therein is executed on a processor of an electronic device provided in an embodiment of the present application, the processor of the electronic device executes the steps in the image recognition-based gait method provided in the present application. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.
[0070] The present application also provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes various optional implementations of the above-mentioned budget control method.
[0071] The above is a detailed introduction to a budget control and system provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for technical personnel in this field, according to the idea of the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.
[0072] It should be noted that when the above embodiments of the present application are applied to specific products or technologies, the relevant data of the user is involved, and the user's permission or consent is required, and the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions.
Claims
1. A budget control method, characterized in that: The specific steps include: Step 1: Collect expense data and collect initial travel expense data a1; Step 2: First preprocessing, performing first preprocessing on the initial travel expense data a1 collected in step 1 to obtain processed data a2; Step 3: Collect personnel data, collect initial business trip personnel data a3; Step 4: Second preprocessing, performing second preprocessing on the initial business traveler data a3 collected in step 3 to obtain processed data a4; Step 5: Database establishment, import the pre-processed data a2 and a4 into the database, and process them to obtain the budget cost database data a5; Step 6: Historical data collection, collect historical travel expense data and obtain a6 after processing; Step 7: Abnormal expense detection, analyzing and comparing the historical travel expense data a6 with the database data a5, identifying abnormal expense data, and marking them to obtain marked data a7; Step 8: Output the results and confirm the budget reimbursement.
2. The budget control method according to claim 1, characterized in that: Before collecting the travel expenses a1, it also includes: data b1 collected after dividing each city, and the data b1 includes transportation cost data c1, catering data c2, accommodation data c3 and communication data c4.
3. The budget control method according to claim 1, characterized in that: Before collecting the business trip personnel data a3, it also includes: collecting the rank status data of all personnel to obtain data b2, which includes position level data d1, age level data d2, gender data d3, length of service data d4 and business trip frequency data d5.
4. The budget control method according to claim 2, characterized in that: The first preprocessing is data cleaning, which involves cleaning and organizing the collected data a1, including removing duplicate data, processing missing values and outliers, etc., to ensure the accuracy and completeness of the data, which is data a2.
5. The budget control method according to claim 4, characterized in that: Cleaning the data includes: Handle missing values, check if there are missing values in the data, and use interpolation methods to fill in missing values; Handling duplicate values: Detect and handle duplicate values in data, using unique identifiers to remove duplicates; Dealing with outliers, identifying and dealing with outliers in the data, using the method of adding or subtracting several times the standard deviation of the mean to identify and deal with outliers.
6. The budget control method according to claim 5, characterized in that: The abnormal value processing may also include outlier processing: for abnormal values that are obviously deviated from the normal range, they may be replaced with reasonable values.
7. A budget control method processing system, characterized in that: The budget control method processing system comprises: The expense data collection module is used to collect initial travel expense data a1; A first preprocessing module performs a first preprocessing on the collected initial travel expense data a1 to obtain processed data a2; The personnel data collection module collects the initial business trip personnel data a3; A second preprocessing module performs a second preprocessing on the collected initial business traveler data a3 to obtain processed data a4; The database establishment module imports the pre-processed data a2 and a4 into the database and processes them to obtain the budget cost database data a5; Historical data collection module, historical data collection, collects historical travel expense data and obtains a6 after processing; Abnormal expense detection: analyze and compare the historical travel expense data a6 with the database data a5, identify abnormal expense data, and mark them to obtain marked data a7; Output result module to confirm budget reimbursement.
8. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and the processor is used to run the computer program in the memory to execute the steps in the budget control method according to any one of claims 1 to 7.
9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor to execute the steps in the budget control method according to any one of claims 1 to 7.