Abstract
In order to improve the economic management effect of large enterprises, a decision support system for economic management of large enterprises based on artificial intelligence is designed. The system hardware and software are designed, respectively. The system hardware consists of basic information module, business management module, personnel management module, salary and welfare management module, system management module, and database module. With the support of artificial intelligence technology, build a BP neural network model, and the model was trained, through continuous learning rate adjustment; in the process of training error lower sales forecast results, according to the result of prediction in enterprise comprehensive benefit maximization as the goal, set up large enterprises economic management decision-making model, large enterprise economic management decision-making algorithm design. The test results show that the system has good fault tolerance, reliability, robustness, and high efficiency, the system response time is short, the decision accuracy is high, and the practical application effect is good.
Highlights
For the design of decision support system for large enterprises’ economic management, some excellent research results have emerged in related fields
Based on the analysis of large data oriented decision support system for the management of large enterprise economic system, on the basis of the major advantages of the proposed enterprise relying on big data to construct the concrete strategy of enterprise decision support system for the management of the economy, including the business layer, network layer, and data layer, policymakers aim to enhance its decision support efficiency for the enterprise and improve enterprise economic management level
In order to solve all kinds of decision-making problems in the production management of edible fungus enterprises, the production management decision support system of edible fungus enterprises is designed. e unified management of production management information is carried out through the edible fungus data warehouse, and the massive data is analyzed and made by knowledge reasoning
Summary
The basic information of customers can be recorded to facilitate future contact and cooperation. By recording and modifying the basic information of suppliers, enterprises can facilitate contact and cooperation. Suppliers have statistical information management similar to that of customers, and the basic information of suppliers can provide technical support for the future development of the company. Supplier management does not set the function of deleting suppliers, so as to help enterprises master the information of customers and suppliers more comprehensively [12, 13]. In the commodity management function, it is mainly used to record the basic information of commodities and can add, delete, modify, and view operations to help enterprise managers understand the basic situation of commodities
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