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《Journal of Harbin Institute of Technology》 2003-07
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Multi-layer feedforward neural network based on ant colony system

HONG Bing-rong, JIN Fei-hu, GAO Qing-ji (School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China,E-mail; fhjin@0451. com)  
Back Propagation is a kind of feedforwad neural networks widely used in many areas, but it has some shortcomings, such as low-precision solutions, slow search speed and easy convergence to the local minimum points. Ant colony system is a novel simulated evolutionary algorithm. Ant system has positive feedback, distributed computation, and use of a constructive greedy heuristic. These characteristics account for rapid discovery of good solutions and easy to realize distributed computation. The combination of ant system with neural network is adopted so that a nonlinear model can be identified and an inverted pendulum controlled. Simulation results show that extensive mapping ability of neural network and rapid global convergence of ant system can be obtained by combining ant system and neural network.
【Fund】: 国家高技术研究发展计划资助项目(2001AA422270)
【CateGory Index】: TP18
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