Research Article
Intelligent Evaluation System for Economic Level of Modern Enterprises Based on BP Neural Network Optimization Algorithm
@INPROCEEDINGS{10.4108/eai.17-11-2023.2342752, author={Jielin Wang}, title={Intelligent Evaluation System for Economic Level of Modern Enterprises Based on BP Neural Network Optimization Algorithm}, proceedings={Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development, ICSETPSD 2023, 17th-18th November 2023, Coimbatore, Tamilnadu, India}, publisher={EAI}, proceedings_a={ICSETPSD}, year={2024}, month={1}, keywords={bp neural network modern enterprises economic level intelligent assessment}, doi={10.4108/eai.17-11-2023.2342752} }
- Jielin Wang
Year: 2024
Intelligent Evaluation System for Economic Level of Modern Enterprises Based on BP Neural Network Optimization Algorithm
ICSETPSD
EAI
DOI: 10.4108/eai.17-11-2023.2342752
Abstract
Modern enterprises are more active economic organizations in the operation and development of the whole national economy, providing more employment opportunities. Establishing a perfect economic level assessment system for modern enterprises is an important task in the current economic management. This paper is to study the construction of an intelligent assessment system for the economic level of modern enterprises based on the BP neural network optimization algorithm. The basic system of enterprise economic level evaluation is proposed, the artificial neural network model is improved into PSO-BP neural network, the research of modern enterprise economic level intelligent evaluation problem is carried out, the three-layer B/S architecture is designed to implement the modern enterprise economic level intelligent evaluation system, the comparison of PSO-BP neural network and BP algorithm, PSO algorithm solves the slow convergence speed to a certain extent The results show that the PSO algorithm has solved the problem of slow convergence to a certain extent, and the PSO-BP neural network is more accurate and reliable than the BP neural network in evaluating the economic level of modern enterprises.