Modeling for Production Rate Measurement of Hydrocyanic Acid Based on PSONN

摘要：

　　Aimed at the problem that it is difficult to measure production rate of hydrocyanic acid directly.So the soft measurement model of production rate of hydrocyanic acid can be established based on neural networks according to interrelated measurable engineering signals.Before being application to engineering,the soft measurement model is trained by PSO algorithm instead of the fast gradient descent method; Simulations prove that the soft measurement model trained by PSO possesses better measuring accuracy and stronger generalization ability.This kind of soft measurement model can be applied to practical production engineering of hydrocyanic acid.

关键词： PSO Neural Networks Soft Measurement

作者: Tang Zhong-jian Song Miao

作者单位: Electrical Information Engineering Department,Zhengda Software Polytechnic of Chongqing,Chongqing 400056

会议类型: 国际会议

会议名称: the 16th International Conference on Fluid Dynamic and Mechanical & Electrical Control Engineering (第16届流体动力与机电控制工程国际学术会议 (FDMECE2012))

会议地点: 重庆

会议语种:英文

页码: 409-415

在线出版日期: 2012-11-10（万方平台首次上网日期，不代表论文的发表时间）