Title :
Solving the Optimization of Projection Pursuit Model Using Improved Ant Colony Algorithm
Author :
Chen, Guang-Zhou ; Wang, Jia-Quan ; Li, Chuan-Jun
Author_Institution :
Sch. of Resources & Environ. Eng., Hefei Univ. of Technol., Hefei
Abstract :
Projection pursuit was a reducing dimensions treatment method. It was widely used to make the transition from high dimensional problem to one dimensional problem by projection direction. It was usually difficult to search the best projection direction, however it could be solved by an optimization question. Aimed at the prematurity and stagnancy shortages of basic ant colony, some improved countermeasures were put forward. Simulative result indicated that it was applicable and effective to solve the above optimization question based on improved ant colony algorithm.
Keywords :
data reduction; nonlinear programming; pattern classification; pattern clustering; search problems; ant colony optimization algorithm; complicated nonlinear optimization problem; data clustering; projection direction search; projection pursuit classification model; reducing dimension treatment method; Ant colony optimization; Computer architecture; Engineering management; Environmental management; Least squares methods; Newton method; Optimization methods; Pursuit algorithms; Resource management; Technology management; ant colony algorithm; chaos algorithm; projection pursuit model;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.582
