Open AccessEvaluation of Innovation and Entrepreneurship Ability of Computer Majors Based on Neural Network Optimized by Particle Swarm Optimization
Author(s) -
Li Ding,
Xuguang Chai,
Fanjin Zeng
Publication year - 2021
Publication title -
international journal of emerging technologies in learning/international journal: emerging technologies in learning
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.454
H-Index - 24
eISSN - 1868-8799
pISSN - 1863-0383
DOI - 10.3991/ijet.v16i20.26507
Subject(s) - particle swarm optimization , artificial neural network , computer science , process (computing) , artificial intelligence , fuzzy logic , entrepreneurship , machine learning , mathematical optimization , industrial engineering , engineering , mathematics , business , finance , operating system
The current evaluation index systems (EISs) of innovation and entrepreneurship (I&E) ability are not sufficiently systematic, scientific, or practical. To solve the problem, this paper tries to evaluate the I&E ability of computer majors, using neural networks improved by particle swarm optimization (PSO). Firstly, an EIS of 22 second-level indexes under 5 first-level indexes was designed to evaluate the I&E ability of college computer majors. Next, an evaluation model was developed based on fuzzy neural network (FNN), and the corresponding training algorithm was created. Moreover, an improved PSO was introduced to optimize the FNN, and the optimization process was detailed. The proposed model was proved effective through experiments.