猫群优化算法的非线性模型参数估计Non-linear model parameter estimation based on Cat Swarm Optimization
王永弟,孙心宇
摘要(Abstract):
针对现代高精度测量工作中传统的群体智能算法存在的不足,该文提出将猫群算法应用于非线性模型参数估计,从观察模式和捕猎模式两个方面论述了猫群优化算法的基本原理、解算步骤等;最后通过实例分析验证了猫群优化算法在非线性模型参数估计中应用的可行性和优势。
关键词(KeyWords): 猫群优化算法;非线性模型;参数估计;群体智能;进化算法
基金项目(Foundation): 青年科学基金项目(41301400);; 江苏省高校自然科学研究项目(1KJB420002);; 南京信息工程大学科研基金项目(2012x045,S8110063001);; 江苏高校优势学科建设工程资助项目(PAPD)
作者(Author): 王永弟,孙心宇
DOI: 10.16251/j.cnki.1009-2307.2015.09.033
参考文献(References):
- [1]王改革.基于智能算法的目标威胁估计[D].中国科学院研究生院(长春光学精密机械与物理研究所),2013.
- [2]王光彪,杨淑莹,冯帆,等.基于猫群算法的图像分类研究[J].天津理工大学学报:自然科学版,2011,27(5):35-39.
- [3]GLODBERG D E.Genetic Algorithms in Search,Optimization,and Machine Learning[J].Addion Wesley Publishing Company,1989.
- [4]DAVIS L.Handbook of Genetic Algorithms[J].Van Nostrand Reinhold,New York,1991.
- [5]PAN J S,MCINNES F R,JACK M A.Application of Parallel Genetic Algorithm and Property of Multiple Global Optima to VQ Codevector Index Assignment for Noisy Channels[J].Electronics Letters,1996,32(4):296-297.
- [6]KIM K W,GEN M,KIM M H.Adaptive Genetic Algorithms for Multi-resource Constrained Project Scheduling Problem with Multiple Modes[J].International Journal of Innovative Computing,Information&Control,2006,2(1):41-49.
- [7]MAEDA Y,LI Q.Parallel Genetic Algorithm with Adaptive Genetic Parameters Tuned by Fuzzy Reasoning[J].International Journal of Innovative Computing,Information&Control,2005,1(1):95-107.
- [8]DORIGO M,MANIEZZO V,COLORNI A.Ant System:Optimization by a Colony of Cooperating Agents[C]//IEEE Transactions on Systems,Man,and Cybernetics,Part B:Cybernetics.IEEE,1996,26(1):29-41.
- [9]DORIGO M,GAMBARDELLA L M.Ant Colony System:A Cooperative Learning Approach to the Traveling Salesman Problem[C]//IEEE Transactions on Evolutionary Computation.IEEE,1997,1(1):53-66.
- [10]CHU S C,RODDICK J F,PAN J S.Ant Colony System with Communication Strategies[J].Information Sciences,2004,167(1):63-76.
- [11]CHU S C,RODDICK J F,SU C J,et al.Constrained Ant Colony Optimization for Data Clustering[M]//PRICAI 2004:Trends in Artificial Intelligence.Springer Berlin Heidelberg,2004:534-543.
- [12]ANGELINE PJ.Evolutionary Optimization versus Particle Swarm Optimization:Philosophy and Performance Differences[C]//Evolutionary Programming VII.Springer Berlin Heidelberg,1998:601-610.
- [13]SHI Y,EBERHART R.Empirical Study of Particle Swarm Optimization[C]//Proc.of the Congress on Evolutionary Computation,1999:1945-1950.
- [14]KENNEDY J,EBERHART R.Particle Swarm Optimization[J].IEEE International of first Conference on Neural Networks.IEEE,1995:601-610.
- [15]CHANG J F,CHU S C,RODDICK J F,et al.A Parallel Particle Swarm Optimization Algorithm with Communication Strategies[J].Journal of Information Science and Engineering,2005,21(4):809-818.
- [16]IWASAKI N,YASUDA K.Adaptive Particle Swarm Optimization Using Velocity Feedback[J].International Journal of Innovative Computing,Information and Control,2005,1(3):369-380.
- [17]CHU S C,TSAI PW,PAN J S.Cat Swarm Optimization[M]//PRICAI 2006:Trends in Artificial Intelligence.Springer Berlin Heidelberg,2006:854-858.
- [18]CHU S C,TSAI P W.Computational Intelligence Based on the Behavior of Cats[J].International Journal of Innovative Computing,Information and Control,2007,3(1):163-173.
- [19]杨淑莹,张桦.群体智能与仿生计算——Matlab技术实现[M].北京:电子工业出版社,2012.
- [20]王新洲.非线性模型参数估计理论与应用[M].武汉:武汉大学出版社,2002.
- [21]王永弟,许承权.熵权理论在测量平差中的应用[J].测绘通报,2012(11):52-54.