Comparison of Neural Network Algorithms based on Gas Qualitative Analysis

摘要：

For the problem of gas qualitatively identify in the field of gas detection, this paper is based on the multi-sensor and pattern recognition of neural network, the uniform change voltage of the sensor output is simulated by the gradient descent algorithm, the additional momentum algorithm and the LM algorithm of neural network, then compare the three simulation results of the three algorithms, the result proves that the LM algorithm is the optimal algorithm of the data simulation in this paper, in the range of allowable error, completed the gas qualitative identification.

关键词： gas sensor BP neural network qualitative identification

作者: Yu Mingyan Shi Yunbo Zhao Wenjie Feng Qiaohua Wang Xuan Sun Lining

作者单位: Measurement-control Tech & Communications Engineering College,The higher educational key laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province,Harbin University of Science and Technology Harbin,China

会议类型: 国际会议

会议名称: The 6th International Forum on Strategic Technology(IFOST 2011)(第六届国际战略技术论坛)

会议地点: 哈尔滨

会议语种:英文

页码: 1176-1180

在线出版日期: 2011-08-22（万方平台首次上网日期，不代表论文的发表时间）