Dongsheng Qing, Jianjun Li, Qiaoling Deng, Shuai Liu
{"title":"Mining and quantifying the optimal DBH range of loblolly pine with improved particle algorithm","authors":"Dongsheng Qing, Jianjun Li, Qiaoling Deng, Shuai Liu","doi":"10.14311/nnw.2022.32.007","DOIUrl":null,"url":null,"abstract":"In order to fully understand the objective law of height and DBH growth of loblolly pine trees and exploring the best DBH (Diameter at Breast Height) Range for loblolly pine tree height growth, 13 340 loblolly pines with initial DBH between 1 inch and 7 inch were selected from Alabama as research objects, and statistics on its growth from 2000 to 2015. Because particle swarm optimization (PSO) is suitable for solving non-linear problems, the optimal DBH of loblolly pine is transformed into the optimization problem of PSO, which quantifies the optimal DBH range of loblolly pine at different scales by mapping strategy. The experimental results show that the range of the breast diameter suitable for the high growth of the pine tree is concentrated between 3.7 inch and 7.3 inch. The height of the pine tree begins to enter a period of rapid growth from a breast diameter of 3.9 inch (ą0.2 inch ). The tree height growth rate reached a maximum at a breast diameter of 6.4 inch (ą0.6 inch ), and the tree height entered a slow growth period after the breast diameter of 11.92 inch (ą0.3 inch). In general, when the breast diameter exceeds 15.26 inch (ą0.3 inch), the height of the pine tree stops growing.","PeriodicalId":49765,"journal":{"name":"Neural Network World","volume":"1 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neural Network World","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.14311/nnw.2022.32.007","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
In order to fully understand the objective law of height and DBH growth of loblolly pine trees and exploring the best DBH (Diameter at Breast Height) Range for loblolly pine tree height growth, 13 340 loblolly pines with initial DBH between 1 inch and 7 inch were selected from Alabama as research objects, and statistics on its growth from 2000 to 2015. Because particle swarm optimization (PSO) is suitable for solving non-linear problems, the optimal DBH of loblolly pine is transformed into the optimization problem of PSO, which quantifies the optimal DBH range of loblolly pine at different scales by mapping strategy. The experimental results show that the range of the breast diameter suitable for the high growth of the pine tree is concentrated between 3.7 inch and 7.3 inch. The height of the pine tree begins to enter a period of rapid growth from a breast diameter of 3.9 inch (ą0.2 inch ). The tree height growth rate reached a maximum at a breast diameter of 6.4 inch (ą0.6 inch ), and the tree height entered a slow growth period after the breast diameter of 11.92 inch (ą0.3 inch). In general, when the breast diameter exceeds 15.26 inch (ą0.3 inch), the height of the pine tree stops growing.
期刊介绍:
Neural Network World is a bimonthly journal providing the latest developments in the field of informatics with attention mainly devoted to the problems of:
brain science,
theory and applications of neural networks (both artificial and natural),
fuzzy-neural systems,
methods and applications of evolutionary algorithms,
methods of parallel and mass-parallel computing,
problems of soft-computing,
methods of artificial intelligence.