Title: Landscape architecture environmental adaptability evaluation model based on improved genetic algorithm

Authors: Chunyan Li

Addresses: College of Tourism and Planning, Pingdingshan University, Pingdingshan, Henan, 467000, China

Abstract: In view of the fact that many environmental factors of landscape architecture are not considered in the evaluation model of landscape architecture environmental adaptability, which leads to low accuracy and long evaluation time, an evaluation model of landscape architecture environmental adaptability based on improved genetic algorithm is proposed. The real vector coding is used to select individual population, and the maximum and average fitness difference is solved to obtain the population entropy; the iterative crossover probability and mutation probability are used to realise the adaptive adjustment, and the genetic algorithm is improved by combining with the optimal retention strategy. Based on the improved adaptive genetic algorithm, the environmental adaptability evaluation system and membership functions were constructed, the weight of landscape environmental factors was determined, and the landscape environmental adaptability evaluation model was designed. The results show the highest accuracy is 95%, and the shortest evaluation time is 0.39 s.

Keywords: improved genetic algorithm; population entropy; diversity measurement; landscape environment; adaptability evaluation.

DOI: 10.1504/IJETM.2022.120729

International Journal of Environmental Technology and Management, 2022 Vol.25 No.1/2, pp.77 - 94

Received: 26 Feb 2021
Accepted: 19 May 2021

Published online: 04 Feb 2022 *

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