Operation management system based on merchant management

Abstract

The invention relates to the technical field of commercial tenant management, in particular to an operation management system based on commercial tenant management, which comprises a user management module, the user management module comprises roles such as a system administrator, a commercial tenant administrator and a common commercial tenant, and each role has different operation authorities. The user management module is in coupling connection with a merchant information management module, and the merchant information management module is in coupling connection with a commodity management module. The operation management system based on commercial tenant management solves the problem that a commercial tenant management system stores a large amount of commercial tenant data, including customer information, sales data and the like. If system security measures are not in place, data leakage and information security risks may occur, a merchant management system is poor in performance when meeting requirements of different industries and different scales of merchants, customized function adjustment cannot be carried out according to actual conditions, interface design of part of systems is not visual enough, the operation process is complex, and the merchant management system is inconvenient to use. And the user feels confused during use, and the management efficiency is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of merchant management, and in particular to an operation management system based on merchant management. Background Art

[0002] The merchant management and operation management system is a software system used to help enterprises manage merchant information and data. It covers multiple aspects such as merchant information management, business management, statistical analysis and customer relationship management. The merchant management and operation management system integrates and optimizes enterprise resources, improves the automation and intelligence level of business processes, and thus helps enterprises achieve efficient, orderly and intelligent management of the operation process. It is suitable for enterprises of all sizes, especially those in the retail, catering, service and other industries that need to manage a large amount of merchant information and data. Through automated and intelligent management methods, the efficiency and accuracy of merchant management are improved. Advanced encryption technology and permission control mechanisms are adopted to ensure the security and confidentiality of merchant data. The system has good scalability and can be customized and expanded according to the specific needs of the enterprise. The system interface is intuitively designed and the operation process is simple, which is convenient for users to quickly get started and use. Merchants can use the system's commodity management function to implement refined management of commodities and improve sales efficiency and profits. Merchants can manage dishes, inventory and orders through the system to improve the operating efficiency and user experience of the restaurant. Merchants can use the system's customer relationship management function to achieve effective communication and interaction with customers and provide personalized services. The merchant management and operation management system is an essential tool for modern merchant management. It covers merchant information management, business management, statistical analysis and customer relationship management. It can help enterprises improve work efficiency and reduce costs, while providing better customer service and business decision support;

[0003] However, the merchant management system in the prior art has the following disadvantages:

[0004] The merchant management system stores a large amount of merchant data, including customer information, sales data, etc. If the system security measures are not in place, there may be data leakage and information security risks;

[0005] The merchant management system performs poorly in adapting to the needs of merchants of different industries and sizes, and cannot be customized according to actual conditions.

[0006] The interface design of some systems is not intuitive enough and the operation process is complicated, which makes users feel confused when using them and reduces management efficiency;

[0007] In view of the above problems, an operation management system based on merchant management is provided. Summary of the invention

[0008] The purpose of the present invention is to provide an operation management system based on merchant management to solve the problems raised in the above background technology. To achieve the above purpose, the present invention provides the following technical solutions: an operation management system based on merchant management, including a user management module, the user management module includes roles such as system administrator, merchant administrator and ordinary merchant, each role has different operation permissions, the user management module is coupled to a merchant information management module, the merchant information management module is coupled to a commodity management module, the commodity management module is coupled to a sales management module, the sales management module is coupled to a data analysis and decision support module, the data analysis and decision support module is coupled to a security and backup module, the security and backup module is coupled to a system upgrade and maintenance module, and the system upgrade and maintenance module is coupled to a customer service and feedback module.

[0009] Preferably, the user management module uses a symmetric encryption algorithm for operation analysis, and the symmetric encryption algorithm includes: generating a key pair:

[0010] Generate a positive integer e and a positive decimal d, so that d*e=(k*10^s*2*π)_N+1, where s is the preset decimal limit, the subscript N indicates that the calculation formula in the brackets will eventually retain N decimal places, and k is a positive integer;

[0011] A positive integer e is saved as a secret key, and an integer n is generated, where n represents the length of the plaintext in decimal. {d, s, N, n} is published as a public key. Encryption process: the encryptor attempts to generate a decimal m so that floor(10^n*cos(m))=M, and the number of decimal places in m does not exceed s, and M is the plaintext. The encryptor calculates C=(cos(d*m))_N, where C is the ciphertext. Decryption process: the multiple angle formula is used to calculate the intermediate value T=(cos(e*d*m))_N, where e is the multiple. From d*e=(k*10^s*2*π)_N+1, the intermediate value T=(cos(((k*10^s*2*π)_N+1)*m))_N=(cos(m))_N is obtained. Calculating floor(10^n*T) obtains the plaintext M.

[0012] Preferably, the cos() function in the encryption process and the decryption process is completely replaced by a sin() function or a tan() function, and the generated positive integer e is an odd number.

[0013] 4. According to claim 2, an operation management system based on merchant management is characterized in that: the method for generating a decimal m comprises: taking out the value of the secret key M at each bit, recorded as (m_0, m_1, ..., m_n1), that is, M = m_n1*10^(n1)+...+m_1*10+m_0; setting an auxiliary variable r=1, trying to generate a decimal m, so that floor(10^r*cos(m))=m_n1; adding 1 to the auxiliary variable r, trying to generate a decimal p, so that floo r(10^r*(cos(m+p)cos(m)))=1, generate multiple b, b∈[9,9], try to change the value of b so that floor(10^r*(cos(m+b*p)))=floor(m_n1*10^(r1)+m_n2*10^(r2)+…+m_0*10^(rn)), update m to m+b*p; repeat the previous step until floor(10^n*cos(m))=M, and get the value of the decimal m.

[0014] Preferably, the user information management module also includes: a merchant information entry module, the merchant information entry module is coupled to a merchant information maintenance module, the merchant information maintenance module is coupled to a merchant classification management module, the merchant classification management module is coupled to a merchant status monitoring module, the merchant status monitoring module is coupled to a merchant information reporting and statistics module, the merchant information reporting and statistics module is coupled to a permission management module, the permission management module is coupled to a GIS (geographic information system) integration module, and the GIS (geographic information system) integration module is coupled to a data backup and recovery module.

[0015] Preferably, the merchant information entry module also includes: a basic information entry module, the basic information entry module is coupled to the legal person and shareholder information entry module, the legal person and shareholder information entry module is coupled to the business information entry module, the business information entry module is coupled to the financial information entry module, the financial information entry module is coupled to the qualification certificate upload module, the qualification certificate upload module is coupled to the custom field module, the custom field module is coupled to the data verification and validation module, and the data verification and validation module is coupled to the information saving and submission module.

[0016] Preferably, the commodity management module includes an inventory warning algorithm, a sales forecasting algorithm, and a commodity classification and recommendation algorithm.

[0017] Preferably, the sales forecasting algorithm comprises the following steps:

[0018] S1. Access the data to remove duplication, clean and verify, integrate data from multiple sources, analyze and count the data, use web crawler technology to obtain corporate sales data, and then use Pandas to pre-process the data based on Python language, and visualize the processed data in the form of charts to provide a reliable data set for the subsequent verification of algorithm models.

[0019] S2, analyze and count the data and give a visual display;

[0020] S3. Based on the processed data, an ARIMA model is constructed, including white noise test, sequence stationarity test and non-stationary sequence processing, model identification and order determination, estimation of unknown parameters in the model, and model optimization. Finally, the obtained ARIMA model is applied to give the sales forecast value of the data set for the next 5 time units;

[0021] S4. Construct the ARIMA_GBDT fusion model. Consider a time series as the sum of the linear part and the nonlinear part. Use the ARIMA model to fit and analyze the time series, extract the linear part in the series, and then use the GBDT algorithm to fit the residual to find the nonlinear information in the series.

[0022] S5. Use Python to take the original data, ARIMA fitting data and residual data as the input value of the algorithm, and obtain the prediction results through the grid parameter adjustment method;

[0023] S6. Using RMSE and MAPE, two evaluation indicators, to compare and quantify the pros and cons of the models, based on the above results, it can be concluded that the ARIMA_GBDT fusion model is superior in trend fitting, short-term prediction accuracy, and overall prediction error.

[0024] Preferably, the inventory early warning algorithm comprises the following steps:

[0025] The on-site working conditions of the equipment are obtained, wherein the on-site working conditions of the equipment include expected faulty components, fault repair time corresponding to the expected faulty components, procurement cycle of the expected faulty components, and current spare parts inventory of the expected faulty components; according to the on-site working conditions of the equipment, a pre-trained inventory safety prediction model is used to perform prediction to obtain an inventory safety prediction result; when the inventory safety prediction result indicates that the equipment spare parts inventory is unsafe, an early warning message is generated, and an information prompt is provided according to the early warning message; wherein the inventory safety prediction model is obtained by training using a machine learning algorithm based on a first training sample, wherein the first training sample includes the on-site working conditions of the equipment and corresponding inventory labels, wherein the on-site working conditions of the equipment include expected faulty components, fault repair time corresponding to the expected faulty components, procurement cycle of the expected faulty components, and current spare parts inventory of the expected faulty components, and the inventory label is used to identify whether the inventory of the expected faulty components is safe.

[0026] Preferably, providing information prompts according to the warning information includes: displaying the warning information on a display screen; and / or, playing a voice corresponding to the warning information; and / or, providing information prompts through indicator lights of different colors.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] In this case, the cooperation of the user management module, merchant information management module, sales management module, data analysis and decision support module, security and backup module, system upgrade and maintenance module, and customer service and feedback module solved the problem that the merchant management system stores a large amount of merchant data, including customer information, sales data, etc. If the system security measures are not in place, there may be data leakage and information security risks, the merchant management system performs poorly in adapting to the needs of merchants of different industries and sizes, and cannot be customized according to actual conditions. Functional adjustments, and the interface design of some systems is not intuitive enough, and the operation process is complicated, which leads to confusion for users when using it and reduces management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A system block diagram of an operation management system based on merchant management of the present invention;

[0030] Figure 2 This is a system block diagram of a user management module of an operation management system based on merchant management of the present invention;

[0031] Figure 3 The present invention is a system block diagram of a merchant data entry module of an operation management system based on merchant management. DETAILED DESCRIPTION

[0032] 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 technical personnel in this field without creative work are within the scope of protection of the present invention.

[0033] See also Figures 1 to 3 The present invention provides a technical solution: an operation management system based on merchant management, including a user management module, providing a user registration function, and allowing users to enter the system through a login interface, allowing system administrators to assign different operation permissions to different users according to the actual needs of merchants, the user management module includes roles such as system administrators, merchant administrators and ordinary merchants, each role has different operation permissions, the user management module is coupled with a merchant information management module, allowing merchant administrators or merchants themselves to enter the merchant's basic information, such as merchant name, address, contact information, etc., providing merchant information modification, deletion and query functions to ensure the accuracy and timeliness of merchant information, the merchant information management module is coupled with a commodity management module, allowing merchants to enter the basic information of commodities, such as commodity name, price, inventory, etc., providing commodity classification addition, modification and deletion functions, and facilitating merchants to classify and manage commodities, commodity inventory management: real-time monitoring of commodity inventory, providing inventory warning functions, and ensuring the adequacy of commodity inventory, the commodity management module is coupled with a sales management module, providing order entry, modification, query and deletion functions, and facilitating merchants to view and manage order information, The sales management module conducts statistical analysis on sales data, provides sales reports and sales trend forecasts, and helps merchants develop sales strategies. The sales management module is coupled with a data analysis and decision support module, which uses data mining technology to conduct in-depth analysis of merchant data, explore potential business opportunities, and provide decision support to merchants based on the data analysis results, such as marketing strategy formulation, inventory management suggestions, etc. The data analysis and decision support module is coupled with a security and backup module, which uses advanced encryption algorithms to encrypt and store merchant data to ensure data security, provides multi-level permission control functions to ensure that only authorized users can access sensitive data, regularly backs up merchant data, and provides data recovery functions to prevent data loss or damage. The security and backup module is coupled with a system upgrade and maintenance module, which provides system upgrade functions to ensure that the system can keep up with technological development and changes in merchant needs, and provides daily maintenance functions such as system optimization and vulnerability repair to ensure system stability and reliability. The system upgrade and maintenance module is coupled with a customer service and feedback module, which provides online customer service functions to facilitate merchants to consult and solve problems at any time, and allows users to submit feedback on the system so that the system can be continuously improved and optimized.

[0034] In this embodiment, the user management module uses a symmetric encryption algorithm for operation analysis. The symmetric encryption algorithm includes: generating a key pair:

[0035] Generate a positive integer e and a positive decimal d, so that d*e=(k*10^s*2*π)_N+1, where s is the preset decimal limit, the subscript N indicates that the calculation formula in the brackets will eventually retain N decimal places, and k is a positive integer;

[0036] A positive integer e is saved as a secret key, and an integer n is generated, where n represents the length of the plaintext in decimal. {d, s, N, n} is published as a public key. Encryption process: the encryptor attempts to generate a decimal m so that floor(10^n*cos(m))=M, and the number of decimal places in m does not exceed s, and M is the plaintext. The encryptor calculates C=(cos(d*m))_N, where C is the ciphertext. Decryption process: the multiple angle formula is used to calculate the intermediate value T=(cos(e*d*m))_N, where e is the multiple. From d*e=(k*10^s*2*π)_N+1, the intermediate value T=(cos(((k*10^s*2*π)_N+1)*m))_N=(cos(m))_N is obtained. Calculating floor(10^n*T) obtains the plaintext M.

[0037] In this embodiment, the cos() function in the encryption process and the decryption process is completely replaced by the sin() function or the tan() function, and the generated positive integer e is an odd number.

[0038] In this embodiment, the method for generating a decimal m includes: taking out the value of the secret key M at each bit, recorded as (m_0, m_1, ..., m_n1), that is, M = m_n1*10^(n1)+...+m_1*10+m_0; setting the auxiliary variable r=1, trying to generate a decimal m, so that floor(10^r*cos(m))=m_n1; adding 1 to the auxiliary variable r, trying to generate a decimal p, so that floor(10^r*(cos(m+ p)cos(m)))=1, generate multiple b, b∈[9,9], try to change the value of b so that floor(10^r*(cos(m+b*p)))=floor(m_n1*10^(r1)+m_n2*10^(r2)+…+m_0*10^(rn)), update m to m+b*p; repeat the previous step until floor(10^n*cos(m))=M, and get the value of the decimal m.

[0039] In this embodiment, the user information management module also includes: a merchant information entry module, which allows the merchant administrator or the merchant himself to enter the merchant's basic information, such as the merchant's name, address, contact information (such as telephone, email), legal representative, registered capital, business scope, business hours, etc., and provides a data verification function to ensure that the entered merchant information is accurate. The merchant information entry module is coupled with a merchant information maintenance module, which provides merchant information modification, deletion and query functions to ensure the accuracy and timeliness of merchant information and supports batch operations, such as batch update of merchant information, batch deletion of invalid merchants, etc. The merchant information maintenance module is coupled with a merchant classification management module, which classifies merchants according to factors such as the merchant's business type, industry attributes or geographical location, allowing administrators to create, modify and delete classifications to better organize and manage merchant information. The merchant classification management module is coupled with a merchant status monitoring module, which monitors the merchant's operating status in real time, such as whether it is online, whether it is open for business, etc., and provides merchant status reminder functions, such as merchant abnormal status alarm, legal The merchant status monitoring module is coupled with the merchant information reporting and statistics module, which generates various reports and statistical data based on the merchant information, such as merchant quantity statistics, merchant type distribution, merchant sales analysis, etc. It supports custom reports and export functions, which is convenient for administrators to use report data for analysis and decision-making. The merchant information reporting and statistics module is coupled with the permission management module to set permissions for different user roles to ensure that only authorized users can access and modify merchant information, record user operation logs, and facilitate tracking and auditing user behavior. The permission management module is coupled with the GIS (geographic information system) integration module, which combines merchant information with GIS maps to achieve visual management of merchant geographic locations and provide query and analysis functions based on geographic location, such as finding nearby merchants, analyzing merchant distribution, etc. The GIS (geographic information system) integration module is coupled with the data backup and recovery module, which regularly backs up merchant information data to ensure data reliability and security, and provides data recovery functions to deal with possible data loss or damage.

[0040] In this embodiment, the merchant information entry module also includes: a basic information entry module, the basic information entry module is coupled to the legal person and shareholder information entry module, the legal person and shareholder information entry module is coupled to the business information entry module, the business information entry module is coupled to the financial information entry module, the financial information entry module is coupled to the qualification certificate upload module, the qualification certificate upload module is coupled to the custom field module, the custom field module is coupled to the data verification and validation module, and the data verification and validation module is coupled to the information storage and submission module.

[0041] In this embodiment, the commodity management module includes an inventory warning algorithm, a sales forecasting algorithm, and a commodity classification and recommendation algorithm.

[0042] In this embodiment, the sales prediction algorithm includes the following steps:

[0043] S1. Access the data to remove duplication, clean and verify, integrate data from multiple sources, analyze and count the data, use web crawler technology to obtain corporate sales data, and then use Pandas to pre-process the data based on Python language, and visualize the processed data in the form of charts to provide a reliable data set for the subsequent verification of algorithm models.

[0044] S2, analyze and count the data and give a visual display;

[0045] S3. Based on the processed data, an ARIMA model is constructed, including white noise test, sequence stationarity test and non-stationary sequence processing, model identification and order determination, estimation of unknown parameters in the model, and model optimization. Finally, the obtained ARIMA model is applied to give the sales forecast value of the data set for the next 5 time units;

[0046] S4. Construct the ARIMA_GBDT fusion model. Consider a time series as the sum of the linear part and the nonlinear part. Use the ARIMA model to fit and analyze the time series, extract the linear part in the series, and then use the GBDT algorithm to fit the residual to find the nonlinear information in the series.

[0047] S5. Use Python to take the original data, ARIMA fitting data and residual data as the input value of the algorithm, and obtain the prediction results through the grid parameter adjustment method;

[0048] S6. Using RMSE and MAPE, two evaluation indicators, to compare and quantify the pros and cons of the models, based on the above results, it can be concluded that the ARIMA_GBDT fusion model is superior in trend fitting, short-term prediction accuracy, and overall prediction error.

[0049] In this embodiment, the inventory warning algorithm includes the following steps:

[0050] The on-site working conditions of the equipment are obtained, and the on-site working conditions of the equipment include expected faulty parts, the fault repair time corresponding to the expected faulty parts, the procurement cycle of the expected faulty parts, and the current spare parts inventory of the expected faulty parts; according to the on-site working conditions of the equipment, a pre-trained inventory safety prediction model is used to predict and obtain an inventory safety prediction result; when the inventory safety prediction result indicates that the equipment spare parts inventory is unsafe, an early warning information is generated, and an information prompt is provided according to the early warning information; wherein, the inventory safety prediction model is trained by using a machine learning algorithm according to a first training sample, and the first training sample includes the on-site working conditions of the equipment and the corresponding inventory labels, and the on-site working conditions of the equipment include expected faulty parts, the fault repair time corresponding to the expected faulty parts, the procurement cycle of the expected faulty parts, and the current spare parts inventory of the expected faulty parts, and the inventory labels are used to identify whether the inventory of the expected faulty parts is safe.

[0051] In this embodiment, providing information prompts according to the warning information includes: displaying the warning information on a display screen; and / or, playing a voice corresponding to the warning information; and / or, providing information prompts through indicator lights of different colors.

[0052] The above shows and describes the basic principles, main features and advantages of the present invention. Technical personnel in this industry should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not used to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An operation management system based on merchant management, characterized in that: It includes a user management module, which includes roles such as system administrator, merchant administrator and ordinary merchant, each role has different operation permissions, the user management module is coupled to the merchant information management module, the merchant information management module is coupled to the commodity management module, the commodity management module is coupled to the sales management module, the sales management module is coupled to the data analysis and decision support module, the data analysis and decision support module is coupled to the security and backup module, the security and backup module is coupled to the system upgrade and maintenance module, and the system upgrade and maintenance module is coupled to the customer service and feedback module.

2. The operation management system based on merchant management according to claim 1, characterized in that: The user management module uses a symmetric encryption algorithm to perform calculation analysis, and the symmetric encryption algorithm includes: generating a key pair: Generate a positive integer e and a positive decimal d, so that d*e=(k*10^s*2*π)_N+1, where s is the preset decimal limit, the subscript N indicates that the calculation formula in the brackets will eventually retain N decimal places, and k is a positive integer; A positive integer e is saved as a secret key, and an integer n is generated, where n represents the length of the plaintext in decimal. {d, s, N, n} is published as a public key. Encryption process: the encryptor attempts to generate a decimal m so that floor(10^n*cos(m))=M, and the number of decimal places in m does not exceed s, and M is the plaintext. The encryptor calculates C=(cos(d*m))_N, where C is the ciphertext. Decryption process: the multiple angle formula is used to calculate the intermediate value T=(cos(e*d*m))_N, where e is the multiple. From d*e=(k*10^s*2*π)_N+1, the intermediate value T=(cos(((k*10^s*2*π)_N+1)*m))_N=(cos(m))_N is obtained. Calculating floor(10^n*T) obtains the plaintext M.

3. The operation management system based on merchant management according to claim 2, characterized in that: Replace all cos() functions in the encryption and decryption processes with sin() functions or tan() functions, and the generated positive integer e is an odd number.

4. The operation management system based on merchant management according to claim 2, characterized in that: The method for generating a decimal m includes: taking out the value of the secret key M at each bit, recorded as (m_0, m_1, ..., m_n1), that is, M = m_n1*10^(n1)+...+m_1*10+m_0; setting the auxiliary variable r = 1, trying to generate a decimal m, so that floor(10^r*cos(m)) = m_n1; adding 1 to the auxiliary variable r, trying to generate a decimal p, so that floor(10^r*(cos(m+p)c os(m)))=1, generate multiple b, b∈[9,9], try to change the value of b so that floor(10^r*(cos(m+b*p)))=floor(m_n1*10^(r1)+m_n2*10^(r2)+…+m_0*10^(rn)), update m to m+b*p; repeat the previous step until floor(10^n*cos(m))=M, and get the value of the decimal m.

5. The operation management system based on merchant management according to claim 1, characterized in that: The user information management module also includes: a merchant information entry module, the merchant information entry module is coupled to a merchant information maintenance module, the merchant information maintenance module is coupled to a merchant classification management module, the merchant classification management module is coupled to a merchant status monitoring module, the merchant status monitoring module is coupled to a merchant information reporting and statistics module, the merchant information reporting and statistics module is coupled to a permission management module, the permission management module is coupled to a GIS (geographic information system) integration module, and the GIS (geographic information system) integration module is coupled to a data backup and recovery module.

6. The operation management system based on merchant management according to claim 5, characterized in that: The merchant information entry module also includes: a basic information entry module, the basic information entry module is coupled to a legal person and shareholder information entry module, the legal person and shareholder information entry module is coupled to an operating information entry module, the operating information entry module is coupled to a financial information entry module, the financial information entry module is coupled to a qualification certificate upload module, the qualification certificate upload module is coupled to a custom field module, the custom field module is coupled to a data verification and validation module, and the data verification and validation module is coupled to an information storage and submission module.

7. The operation management system based on merchant management according to claim 1, characterized in that: The commodity management module includes an inventory warning algorithm, a sales forecasting algorithm, and a commodity classification and recommendation algorithm.

8. The operation management system based on merchant management according to claim 7, characterized in that: The sales forecasting algorithm comprises the following steps: S1. Access the data to remove duplication, clean and verify, integrate data from multiple sources, analyze and count the data, use web crawler technology to obtain corporate sales data, and then use Pandas to pre-process the data based on Python language, and visualize the processed data in the form of charts to provide a reliable data set for the subsequent verification of algorithm models. S2, analyze and count the data and give a visual display; S3. Based on the processed data, an ARIMA model is constructed, including white noise test, sequence stationarity test and non-stationary sequence processing, model identification and order determination, estimation of unknown parameters in the model, and model optimization. Finally, the obtained ARIMA model is applied to give the sales forecast value of the data set for the next 5 time units; S4. Construct the ARIMA_GBDT fusion model. Consider a time series as the sum of the linear part and the nonlinear part. Use the ARIMA model to fit and analyze the time series, extract the linear part in the series, and then use the GBDT algorithm to fit the residual to find the nonlinear information in the series. S5. Use Python to take the original data, ARIMA fitting data and residual data as the input value of the algorithm, and obtain the prediction results through the grid parameter adjustment method; S6. Using RMSE and MAPE, two evaluation indicators, to compare and quantify the pros and cons of the models, based on the above results, it can be concluded that the ARIMA_GBDT fusion model is superior in trend fitting, short-term prediction accuracy, and overall prediction error.

9. The operation management system based on merchant management according to claim 7, characterized in that: The inventory early warning algorithm comprises the following steps: Acquire the equipment on-site working conditions, wherein the equipment on-site working conditions include an expected fault component, a fault repair time corresponding to the expected fault component, a procurement cycle of the expected fault component, and a current spare parts inventory of the expected fault component; According to the equipment on-site working conditions, a pre-trained inventory safety prediction model is used to perform prediction to obtain an inventory safety prediction result; When the inventory safety prediction result indicates that the equipment spare parts inventory is unsafe, a warning message is generated, and an information prompt is given according to the warning message; wherein the inventory safety prediction model is trained using a machine learning algorithm based on a first training sample, the first training sample includes equipment site conditions and corresponding inventory labels, the equipment site conditions include expected faulty components, fault repair times corresponding to the expected faulty components, procurement cycles of the expected faulty components, and current spare parts inventory of the expected faulty components, and the inventory labels are used to identify whether the inventory of the expected faulty components is safe.

10. An operation management system based on merchant management according to claim 9, characterized in that: Providing information prompts according to the warning information includes: displaying the warning information on a display screen; and / or, playing a voice corresponding to the warning information; and / or, providing information prompts through indicator lights of different colors.

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