论文信息 - An Optimization for Identification System of the Simulated Infrared Spectra of Polluted Gasses Using Genetic Algorithm

An Optimization for Identification System of the Simulated Infrared Spectra of Polluted Gasses Using Genetic Algorithm

A new method that the hidden nodes of the neural network are chosen by the genetic algorithm is proposed in this paper. The experimental results show that the appropriate hidden nodes can be selected by the genetic algorithm, and the results from the identification indicate that the system is quite efficient for identifying multi-objective polluted infrared spectra.

Zhang Jun | Liu Meijuan | Yuan Shuai | Jing Lei

[1] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[2] D. E. Goldberg,et al. Genetic Algorithms in Search , 1989 .

[3] Jun Zhang,et al. [Fast algorithm for feature extraction and identification of infrared spectra of polluted gases]. , 2006, Guang pu xue yu guang pu fen xi = Guang pu.

[4] Shuo Wang,et al. A Genetic-Algorithm-Based Two-Stage Learning Scheme for Neural Networks , 2010, 2010 International Conference on e-Education, e-Business, e-Management and e-Learning.

[5] Cai Kai-yuan. A Genetic-Algorithm-based Two-Stage Learning Scheme for Neural Networks , 2003 .

[6] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .