太阳成8722(中国)有限公司-GREEN NO.1

标题：AITSO: A Tool for Spatial Optimization Based on Artificial Immune Systems作者：Zhao, Xiang; Liu, Yaolin; Liu, Dianfeng; Ma, Xiaoya

来源出版物：COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 文献号：549832 DOI：10.1155/2015/549832 出版年：2015

摘要：A great challenge facing geocomputation and spatial analysis is spatial optimization, given that it involves various high-dimensional, nonlinear, and complicated relationships. Many efforts have been made with regard to this specific issue, and the strong ability of artificial immune system algorithms has been proven in previous studies. However, user-friendly professional software is still unavailable, which is a great impediment to the popularity of artificial immune systems. This paper describes a free, universal tool, named AITSO, which is capable of solving various optimization problems. It provides a series of standard application programming interfaces (APIs) which can (1) assist researchers in the development of their own problem-specific application plugins to solve practical problems and (2) allow the implementation of some advanced immune operators into the platform to improve the performance of an algorithm. As an integrated, flexible, and convenient tool, AITSO contributes to knowledge sharing and practical problem solving. It is therefore believed that it will advance the development and popularity of spatial optimization in geocomputation and spatial analysis.

入藏号：WOS:000348360800001

文献类型：Article

语种：English

扩展关键词：PARTICLE SWARM OPTIMIZATION; LAND-USE ALLOCATION; TRAVELING SALESMAN PROBLEM; CLONAL SELECTION; CONCEPTUAL-FRAMEWORK; MONITORING NETWORK; DEVELOPING-AREA; GIS; ALGORITHM; INTELLIGENCE

通讯作者地址：Ma, Xiaoya; Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址：xiaoyama@whu.edu.cn

地址：

[Zhao, Xiang; Liu, Yaolin; Liu, Dianfeng; Ma, Xiaoya] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Liu, Yaolin] Wuhan Univ, Minist Educ, Key Lab Geog Informat Syst, Wuhan 430079, Peoples R China.

研究方向：Mathematical & Computational Biology; Neurosciences & Neurology

ISSN：1687-5265

eISSN:1687-5273