| 基于蚁群优化算法的线状目标简化模型 |
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| 引用本文： | 郑春燕,郭庆胜,胡华科.基于蚁群优化算法的线状目标简化模型[J].测绘学报,2011,40(5):635-638. |
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| 作者姓名： | 郑春燕 郭庆胜 胡华科 |
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| 作者单位： | 1. 嘉应学院地理科学与旅游学院,广东梅州,514015
2. 武汉大学资源与环境科学学院,湖北武汉,430079 |
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| 基金项目： | 国家自然科学基金(41071289;41101351);广东省自然科学基金(9451401501004135);梅州市科技局、嘉应学院联合资助(2009KJZ03),嘉应学院地理科学重点扶持学科(GIS方向)资助,嘉应学院中青年骨干教师重点培养工程基金 |
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| 摘 要： | 基于蚁群优化算法的基本原理，分析线状目标简化过程中所需满足的约束条件，建立具体的算法设计模型，并引入长期禁忌表和局部搜索策略以提高算法的运算效率，给出解题的关键步骤。最后对该算法进行测试，简化结果表明将蚁群优化算法用于线状目标的简化，能较好地保持线状目标的几何形状特征，在顾及长度偏差和矢量偏差的同时有较高的压缩率。与道格拉斯算法简化结果对比表明，在相同的几何限差内蚁群优化算法所得目标函数值更佳。
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| 关 键 词： | 线状目标 蚁群优化 约束条件 简化 |
The Simplification Model of Linear Objects Based on Ant Colony Optimization Algorithm |
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| ZHENG Chunyan,GUO Qingsheng,HU Huake.The Simplification Model of Linear Objects Based on Ant Colony Optimization Algorithm[J].Acta Geodaetica et Cartographica Sinica,2011,40(5):635-638. |
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| Authors: | ZHENG Chunyan GUO Qingsheng HU Huake |
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| Institution: | 1.School of Geographic Science and Tourism,Jiaying University,Meizhou 514015,China;2.School of Resources and Environment Science,Wuhan University,Wuhan 430079,China |
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| Abstract: | According to the purpose for simplifying linear objects,the standards on map production and the basic principles of ant colony optimization algorithm,the simplification of linear objects is explained as a kind of combinatorial optimization problem,and the constraints that should be satisfied in the simplifying process are described by mathematical formulae at first.Then a model of automated simplification using ant colony optimization algorithm is put forward in detail and the key steps are given.In order to improve operational efficiency of the algorithm,long-term taboo list and the local search strategy are introduced.Finally,the algorithm is tested and compared with Douglas algorithm,the results demonstrate that the proposed model to the automatic generalization of linear objects is feasible and effective,and the objective function values obtained from ACO algorithm are better within the same geometric tolerance.Using the proposed algorithm the basic geometric characteristics of linear objects are maintained,and a higher compression ratio is achieved while taking into account length deviation and vector deviation. |
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| Keywords: | linear objects ant colony optimization constraints simplification |
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