{"title":"A Harris Hawks optimization-based cellular automata model for urban growth simulation","authors":"Yuan Ding, Hengyi Zheng, Fuming Jin, Dongming Chen, Xinyu Huang","doi":"10.1007/s12145-024-01399-z","DOIUrl":null,"url":null,"abstract":"<p>This paper proposes an innovative cellular automata model based on the Harris Hawk Optimization (HHO) algorithm. HHO is an intelligent optimization algorithm inspired by the cooperative hunting behavior of Harris’s hawks, demonstrating excellent optimization efficiency in spatial searches. Combining the HHO algorithm with the CA model, we establish the HHO-CA model for simulating urban growth in Guangzhou, China. The simulation achieves a total accuracy of 91.95%, an accuracy of urban cells of 82.43%, and a Kappa coefficient of 0.7441, all superior to the Null model. Furthermore, comparing the HHO-CA model with other representative CA models, the HHO-CA model outperforms in total accuracy, accuracy of urban cells, and Kappa coefficient, showcasing significant advantages in using the HHO algorithm to mine transition rules during the simulation of urban growth processes.</p>","PeriodicalId":49318,"journal":{"name":"Earth Science Informatics","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Earth Science Informatics","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s12145-024-01399-z","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes an innovative cellular automata model based on the Harris Hawk Optimization (HHO) algorithm. HHO is an intelligent optimization algorithm inspired by the cooperative hunting behavior of Harris’s hawks, demonstrating excellent optimization efficiency in spatial searches. Combining the HHO algorithm with the CA model, we establish the HHO-CA model for simulating urban growth in Guangzhou, China. The simulation achieves a total accuracy of 91.95%, an accuracy of urban cells of 82.43%, and a Kappa coefficient of 0.7441, all superior to the Null model. Furthermore, comparing the HHO-CA model with other representative CA models, the HHO-CA model outperforms in total accuracy, accuracy of urban cells, and Kappa coefficient, showcasing significant advantages in using the HHO algorithm to mine transition rules during the simulation of urban growth processes.
期刊介绍：
The Earth Science Informatics [ESIN] journal aims at rapid publication of high-quality, current, cutting-edge, and provocative scientific work in the area of Earth Science Informatics as it relates to Earth systems science and space science. This includes articles on the application of formal and computational methods, computational Earth science, spatial and temporal analyses, and all aspects of computer applications to the acquisition, storage, processing, interchange, and visualization of data and information about the materials, properties, processes, features, and phenomena that occur at all scales and locations in the Earth system’s five components (atmosphere, hydrosphere, geosphere, biosphere, cryosphere) and in space (see "About this journal" for more detail). The quarterly journal publishes research, methodology, and software articles, as well as editorials, comments, and book and software reviews. Review articles of relevant findings, topics, and methodologies are also considered.
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