基于粒子群算法的矢量元胞自动机转换规则获取  

Discovery Transition Rules of Vector Cellular Automata by Using Particle Swarm Optimization

作　　者：沈泉飞[1] 曹敏[2] 董玉军[2] 

机构地区：[1]江苏省基础地理信息中心 [2]南京师范大学虚拟地理环境教育部重点实验室

出　　处：《现代测绘》2015年第3期11-14,共4页Modern Surveying and Mapping

基　　金：国家自然科学基金资助项目(41101349);江苏省高校自然科学研究资助项目(13KJB420003)

摘　　要：本文提出了一种基于粒子群算法来自动获取矢量元胞自动机转换规则的新方法。采用粒子群算法所提取的转换规则毋需通过数学公式来表达,能更方便和准确地描述自然界中的复杂关系,并且这些规则比数学公式更容易让人理解。以丹阳市城市扩展为例,使用粒子群算法挖掘元胞自动机转换规则模拟该研究区域的城市扩展过程,并对模拟结果进行了精度评价。It presents a new method to discover transition rules for geographic vector cellular automata based on particle swarm optimization.The translation rules discovered by particle swarm optimization do not need to be expressed by mathematical formula,that can be more convenient and accurately describe the complex relationship of the nature,and these rules are easier to understand than mathematical formulas.It takes the expansion of Danyang as an example,the transition rules of cellular automata discovered by particle swarm optimization are used to simulate the urban expansion of the study area.In addition,it evaluates the accuracy of the simulating result.

关 键 词：粒子群算法 元胞自动机 转换规则 城市扩展 

分 类 号：P208[天文地球—地图制图学与地理信息工程]