Cargando…

Artificial Intelligence Network Embedding, Entrepreneurial Intention, and Behavior Analysis for College Students’ Rural Tourism Entrepreneurship

To promote the development of the rural economy and improve entrepreneurship education in colleges and universities, college students’ willingness and behavior toward rural tourism entrepreneurship were investigated in this study. First of all, based on the previous research results, the influencing...

Descripción completa

Detalles Bibliográficos
Autor principal: Kang, Zhonghui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9197385/
https://www.ncbi.nlm.nih.gov/pubmed/35712173
http://dx.doi.org/10.3389/fpsyg.2022.843679
_version_ 1784727394383298560
author Kang, Zhonghui
author_facet Kang, Zhonghui
author_sort Kang, Zhonghui
collection PubMed
description To promote the development of the rural economy and improve entrepreneurship education in colleges and universities, college students’ willingness and behavior toward rural tourism entrepreneurship were investigated in this study. First of all, based on the previous research results, the influencing factor model was determined for college students’ entrepreneurial intention. Second, a questionnaire survey was made to collect data from a university in Xi’an City. Finally, the artificial neural network (ANN), improved by a genetic algorithm (GA) based on an artificial intelligence network, was used to study the relationship between college students’ entrepreneurial intention and behavior, and the simulation was carried out on MATLAB2013b software. The results show that the average evaluation accuracy is 81.13% for 60 groups of data using the unmodified back propagation neural network (BPNN) algorithm, while the average evaluation accuracy is 92.17% for the BPNN algorithm improved and optimized by GA, with an ascent of 11.04%. Therefore, the BPNN algorithm improved and optimized by GA is better than the unmodified BPNN algorithm; It is also feasible and effective in the analysis of influencing factors of college students’ entrepreneurial intention and behavior. The research provides a basis for colleges and universities to carry out entrepreneurship education on a large scale and to cultivate their innovative talents.
format Online
Article
Text
id pubmed-9197385
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-91973852022-06-15 Artificial Intelligence Network Embedding, Entrepreneurial Intention, and Behavior Analysis for College Students’ Rural Tourism Entrepreneurship Kang, Zhonghui Front Psychol Psychology To promote the development of the rural economy and improve entrepreneurship education in colleges and universities, college students’ willingness and behavior toward rural tourism entrepreneurship were investigated in this study. First of all, based on the previous research results, the influencing factor model was determined for college students’ entrepreneurial intention. Second, a questionnaire survey was made to collect data from a university in Xi’an City. Finally, the artificial neural network (ANN), improved by a genetic algorithm (GA) based on an artificial intelligence network, was used to study the relationship between college students’ entrepreneurial intention and behavior, and the simulation was carried out on MATLAB2013b software. The results show that the average evaluation accuracy is 81.13% for 60 groups of data using the unmodified back propagation neural network (BPNN) algorithm, while the average evaluation accuracy is 92.17% for the BPNN algorithm improved and optimized by GA, with an ascent of 11.04%. Therefore, the BPNN algorithm improved and optimized by GA is better than the unmodified BPNN algorithm; It is also feasible and effective in the analysis of influencing factors of college students’ entrepreneurial intention and behavior. The research provides a basis for colleges and universities to carry out entrepreneurship education on a large scale and to cultivate their innovative talents. Frontiers Media S.A. 2022-05-27 /pmc/articles/PMC9197385/ /pubmed/35712173 http://dx.doi.org/10.3389/fpsyg.2022.843679 Text en Copyright © 2022 Kang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Kang, Zhonghui
Artificial Intelligence Network Embedding, Entrepreneurial Intention, and Behavior Analysis for College Students’ Rural Tourism Entrepreneurship
title Artificial Intelligence Network Embedding, Entrepreneurial Intention, and Behavior Analysis for College Students’ Rural Tourism Entrepreneurship
title_full Artificial Intelligence Network Embedding, Entrepreneurial Intention, and Behavior Analysis for College Students’ Rural Tourism Entrepreneurship
title_fullStr Artificial Intelligence Network Embedding, Entrepreneurial Intention, and Behavior Analysis for College Students’ Rural Tourism Entrepreneurship
title_full_unstemmed Artificial Intelligence Network Embedding, Entrepreneurial Intention, and Behavior Analysis for College Students’ Rural Tourism Entrepreneurship
title_short Artificial Intelligence Network Embedding, Entrepreneurial Intention, and Behavior Analysis for College Students’ Rural Tourism Entrepreneurship
title_sort artificial intelligence network embedding, entrepreneurial intention, and behavior analysis for college students’ rural tourism entrepreneurship
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9197385/
https://www.ncbi.nlm.nih.gov/pubmed/35712173
http://dx.doi.org/10.3389/fpsyg.2022.843679
work_keys_str_mv AT kangzhonghui artificialintelligencenetworkembeddingentrepreneurialintentionandbehavioranalysisforcollegestudentsruraltourismentrepreneurship