Purchase management method and system based on business big data

By introducing LSTM algorithm and dynamic association mechanism in the procurement management system, the problems of unstable procurement prediction accuracy and lack of dynamic adjustment of supplier grading in the existing technology are solved, and more efficient procurement management and supply chain coordination are achieved.

CN119692909APending Publication Date: 2025-03-25NANJING RUIFU INFORMATION TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202411752545.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-02
Publication Date
2025-03-25

AI Technical Summary

Technical Problem

The existing procurement management system has unstable accuracy in demand forecasting, and the lack of dynamic adjustment mechanism for supplier hierarchical evaluation, resulting in inefficient procurement management and insufficient supply chain coordination.

Method used

A procurement prediction model is constructed using a long and short-term memory network (LSTM) algorithm, a dynamic correlation mechanism between prediction accuracy and supplier grading is established, and a scientific grading management of suppliers is realized through a scoring system and weighting algorithm, and procurement suggestions are generated in combination with the procurement decision matrix.

Benefits of technology

It improves the accuracy and stability of procurement forecasts, realizes dynamic optimization of supplier management, and improves the automation level and operational efficiency of procurement management.

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Abstract

The invention discloses a purchase management method and system based on business big data, and relates to the technical field of purchase prediction and supplier management, and the method comprises the steps: collecting historical purchase records of a business database, carrying out the preprocessing, generating a preprocessing data set, and constructing and training a purchase prediction model through a long short-term memory (LSTM) network algorithm; the purchase demand is predicted through the purchase prediction model, a demand prediction result is output, and the suppliers are graded through the demand prediction result to form graded suppliers; and generating a purchase suggestion list through the graded suppliers, and sending the purchase suggestion list to the purchase management terminal. According to the invention, the purchase prediction model based on the multilayer LSTM neural network is established, so that the long and short term characteristics of the purchase data are effectively captured and accurately predicted; and in combination with the purchase decision matrix and the differentiation processing strategy, the system automatically generates purchase suggestions and pushes the purchase suggestions to the management terminal through the encryption channel, so that the automation level and the operation efficiency of enterprise purchase management are effectively improved.
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