Optimization of the Development Path of Innovation and Entrepreneurship Education in Applied Universities Based on the Solution of Nonlinear Equations
DOI:
https://doi.org/10.70917/ijcisim-2026-0133Keywords:
nonlinear regression; support vector machine regression; multilayer perceptron; innovation and entrepreneurship educationAbstract
This paper applies nonlinear equations to higher education innovation and entrepreneurship education, aiming to identify the factors influencing the effectiveness of such education and to identify pathways for optimizing it. After completing the research design, the author constructed a nonlinear regression model for the effectiveness of higher education innovation and entrepreneurship education using support vector machine regression and a multi-layer perceptron. The research hypotheses were tested through empirical research. The correlation coefficients between teaching environment, classroom interaction, student performance, teacher performance, teaching system support, and the effectiveness of innovation and entrepreneurship education; between teacher performance and student performance; between teaching system support and teaching environment; and between teaching system support and classroom interaction are all greater than 0.7 and significant at the 0.01 level. Teaching environment, classroom interaction, student performance, teacher performance, and teaching system support positively influence the effectiveness of innovation and entrepreneurship education in higher education institutions. Teaching system support positively influences teaching environment and classroom interaction, and teacher performance positively influences student performance.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Xue Kaili, Simon Kwong Choong Mun

This work is licensed under a Creative Commons Attribution 4.0 International License.