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| Research on Cloud Process Neural Network Model and Algorithm |
| Wang Bing① Li Pan-chi① Yang Dong-li① Yu Xiao-hong② |
①(School of Computer & Information Technology, Northeast Petroleum University, Daqing 163318, China)
②(Exploration and Development Research Institute, Daqing Oilfield Company, Daqing 163712, China) |
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Abstract For modeling and solving problems of complex nonlinear systems whose input/output have uncertainty and are associated with time or process, a cloud process neural network model is built in the paper. It has uncertainty information processing ability by combining process neural network’s processing ability for time-varying signal with cloud model transformation ability between qualitative and quantitative concepts. In addition, the cat swarm optimization algorithm is used to optimize the network structure and parameters simultaneously, and it helps to improve network approximation?and generalization performance. The effective extension of neural networks in time domain and uncertain information processing field is realized. Experimental results verify the effectiveness and feasibility of the model and algorithm.
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Received: 13 March 2014
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Corresponding Authors:
Wang Bing
E-mail: wangbing0812@sina.com
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2015, Vol. 37 
