The Sustainable Rural Industrial Development under Entrepreneurship and Deep Learning from Digital Empowerment

Suwei Gao, Xiaobei Yang (), Huizhen Long, Fengrui Zhang and Qin Xin
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Suwei Gao: Research Institute of China’s Rural Policy and Practice, Ningbo University, Ningbo 315000, China
Xiaobei Yang: School of Tourism Management, Henan Finance University, Zhengzhou 450046, China
Huizhen Long: School of Tourism and Hospitality Management, Hong Kong Polytechnic University, Hong Kong, China
Fengrui Zhang: College of Life Sciences, Sichuan Agricultural University, Ya’an 625014, China
Qin Xin: Faculty of Science and Technology, University of the Faroe Islands, Vestarabryggja 15, FO 100 Torshavn, Faroe Islands, Denmark

Sustainability, 2023, vol. 15, issue 9, 1-19

Abstract: This paper aims to realize the planning of resource utilization and development of rural industries endowed by digitalization under entrepreneurship. First, the global classic practical experience of digitizing rural industries is studied, and the development model of existing rural industries is captured from the perspective of entrepreneurship. Second, the influencing factors of rural industrial development are extracted, the structure of resource development is analyzed, and a Neural Network (NN) model of industrial development aiming at expected per capita annual income is established. In addition, a Genetic Algorithm (GA) is introduced to learn the weights of influencing factors in the model. The structure of the NN is determined through extensive experiments. Finally, conclusions are drawn through the simulation and experiment of NN and GA. Tourism, infrastructure, and transportation planning have weights of 7.79, 5.6, and 6.4, respectively, and these three sectors should be vigorously developed. In the future, the weight values of these factors can be used for reference, and the development of various aspects can be refined. This paper clarifies the core of industrial development in rural revitalization based on the perspective of entrepreneurship. The problem of how to realize the optimal utilization of resources is solved scientifically and rationally through the mathematical model. The introduction of deep learning algorithm models provides data support for resource allocation and industrial planning in the process of digital empowerment of traditional rural industries, which is of great value and significance for exploring digital models for rural industry development.

Keywords: entrepreneurship; sustainable development; deep learning; neural network; industrial planning; digital development (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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