Construction of computer model for enterprise green innovation by PSO-BPNN algorithm and its impact on economic performance.

ABSTRACT: The present work aims to analyze the elements that affect corporate green technology innovation and investigate a method suitable for predicting and evaluating corporate performance. First, the elements of green technology innovation and their relationships are analyzed and explained. Then, the Complex Adaptive System (CAS) theory is introduced. On this basis, a computer model for the driving mechanism system of corporate green technology innovation is constructed on the Recursive Porus Agent Simulation (Repast) platform. Finally, the Backpropagation Neural Network (BPNN) model is optimized by Particle Swarm Optimization (PSO), constituting the PSO-BPNN algorithm to evaluate corporate performance. The results of network training and simulation demonstrate that compared with traditional BPN

SUBMITTER: Zhang X 

PROVIDER: S-EPMC8797208 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature