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Article

A Low-Carbon Decision-Making Algorithm for Water-Spot Tourists, Based on the k-NN Spatial-Accessibility Optimization Model

1
Post-Doctoral Innovative Practice Base of Sichuan Province, Leshan Vocational and Technical College, Leshan 614000, China
2
Institute of Geospatial Information, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China
*
Author to whom correspondence should be addressed.
Academic Editor: David J. Lampert
Water 2022, 14(18), 2920; https://doi.org/10.3390/w14182920
Received: 25 July 2022 / Revised: 2 September 2022 / Accepted: 13 September 2022 / Published: 18 September 2022
(This article belongs to the Special Issue Impacts of Energy Production on Water Resources)
This study presents a low-carbon decision-making algorithm for water-spot tourists, based on the k-NN spatial-accessibility optimization model, to address the problems of water-spot tourism spatial decision-making. The attributes of scenic water spots previously visited by the tourists were knowledge-mined, to ascertain the tourists’ interest-tendencies. A scenic water-spot classification model was constructed, to classify scenic water spots in tourist cities. Then, a scenic water spot spatial-accessibility optimization model was set up, to sequence the scenic spots. Based on the tourists’ interest-tendencies, and the spatial accessibility of the scenic water spots, a spatial-decision algorithm was constructed for water-spot tourists, to make decisions for the tourists, in regard to the tour routes with optimal accessibility and lowest cost. An experiment was performed, in which the tourist city of Leshan was chosen as the research object. The scenic water spots were classified, and the spatial accessibility for each scenic spot was calculated; then, the optimal tour routes with optimal spatial accessibility and the lowest cost were output. The experiment verified that the tour routes that were output via the proposed algorithm had stronger spatial accessibility, and cost less than the sub-optimal ones, and were thus more environmentally friendly. View Full-Text
Keywords: water-spot tourist; spatial decision-making; k-NN algorithm; scenic water-spot classification; spatial accessibility; low-carbon and environmental protection water-spot tourist; spatial decision-making; k-NN algorithm; scenic water-spot classification; spatial accessibility; low-carbon and environmental protection
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MDPI and ACS Style

Zhou, X.; Wen, B.; Su, M.; Tian, J. A Low-Carbon Decision-Making Algorithm for Water-Spot Tourists, Based on the k-NN Spatial-Accessibility Optimization Model. Water 2022, 14, 2920. https://doi.org/10.3390/w14182920

AMA Style

Zhou X, Wen B, Su M, Tian J. A Low-Carbon Decision-Making Algorithm for Water-Spot Tourists, Based on the k-NN Spatial-Accessibility Optimization Model. Water. 2022; 14(18):2920. https://doi.org/10.3390/w14182920

Chicago/Turabian Style

Zhou, Xiao, Bowei Wen, Mingzhan Su, and Jiangpeng Tian. 2022. "A Low-Carbon Decision-Making Algorithm for Water-Spot Tourists, Based on the k-NN Spatial-Accessibility Optimization Model" Water 14, no. 18: 2920. https://doi.org/10.3390/w14182920

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