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Issue title: Special Section: Computational Human Performance Modelling for Human-in-the-Loop Machine Systems
Guest editors: Hoshang Kolivand, Valentina E. Balas, Anand Paul and Varatharajan Ramachandran
Article type: Research Article
Authors: Cui, Li | Zhou, Huiqiu; *
Affiliations: Northeast Agricultural University, Harbin City, Heilongjiang, China
Correspondence: [*] Corresponding author. Huiqiu Zhou, Northeast Agricultural University, Harbin City, Heilongjiang, 150030, China. E-mail: [email protected].
Abstract: The provision of basic public services in rural areas is a necessary condition for promoting farmers, agriculture, and rural development, and has important economic effects. The supply of basic public services in rural areas has an impact on agricultural growth, rural poverty reduction, and farmers’ production and investment, and ultimately directly or indirectly affect farmers’ income and consumption. In order to effectively improve the effectiveness of providing basic public services in rural areas, this study takes rural basic public services as the research object, and analyzes the economic and geographic perspectives, models, and algorithms of supply effectiveness through a literature review. It was found that the research area level needs to be deepened, and the shortcomings of traditional models and algorithms were also found. This article will make full use of the TOPSIS model’s methodological advantages in comprehensive ranking, combine the entropy method with the TOPSIS model, and sort the evaluation objects by approaching the optimal solution, so as to more objectively evaluate the rural basic public service supply in the sample counties. Based on the data aggregation algorithm, with the help of spatial analysis methods, Gini coefficient, and Theil index to further study the spatial distribution characteristics of supply. The research shows that the method has good performance and can be used as a reference for the subsequent related research rural basic services theory.
Keywords: TOPSIS model, data aggregation algorithm , rural basic public services, spatial analysis
DOI: 10.3233/JIFS-189042
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5623-5634, 2020
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