MENG Ke1,2, DONG Zhao-yang2, GAO Xiao-dan1, WANG Hai-ming1, LI Xiao3
（1. Centre for Intelligent Electricity Networks, The University of Newcastle, Callaghan 2308, Australia;2. School of Electrical and Information Engineering, The University of Sydney, Sydney 2006, Australia;3. School of Computer Science and Control Engineering, North University of China, Taiyuan 030051, China）
Abstract： An improved immune algorithm is proposed in this paper. The problems, such as convergence speed and optimization precision, existing in the basic immune algorithm are well addressed. Besides, a fuzzy adaptive method is presented by using the fuzzy system to realize the adaptive selection of two key parameters (possibility of crossover and mutation). By comparing and analyzing the results of several benchmark functions, the performance of fuzzy immune algorithm (FIA) is approved. Not only the difficulty of parameters selection is relieved, but also the precision and stability are improved. At last, the FIA is applied to optimization of the structure and parameters in radial basis function neural network (RBFNN) based on an orthogonal sequential method. And the availability of algorithm is proved by applying RBFNN in modeling in soft sensor of solvent tower.
Key words： immune algorithm; fuzzy system; radial basis function neural network (RBFNN); soft sensor
CLD number： TP273+.4Document code： A
Article ID： 1674-8042（2015）02-0197-08 doi： 10.3969/j.issn.1674-8042.2015.02.016
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模糊免疫算法及其在溶剂脱水塔软测量建模中的应用
孟科1， 2， 董朝阳2， 高晓丹1， 王海明1， 李晓3
（1. Centre for Intelligent Electricity Networks, The University of Newcastle, Callaghan 2308, Australia;2. School of Electrical and Information Engineering, The University of Sydney, Sydney 2006, Australia;3. 中北大学 计算机与控制工程学院， 山西 太原 030051）
摘要： 本文针对基本免疫算法收敛速度慢、 计算精度低等缺点， 提出了模糊免疫算法。 该算法引入模糊技术， 对关键参数(交叉概率和变异概率)实现了模糊自适应调整。 通过标准测试函数实验结果的对比， 其可行性和有效性得到证明， 不仅减轻了原始算法中参数确定存在的困难， 而且提高了算法的计算速度和精度。 其次， 本文将模糊免疫算法用于径向基神经网络的训练， 并将该神经网络应用于溶剂脱水塔软测量模型。 仿真实验证明， 模糊免疫算法优化的径向基函数神经网络具有良好的泛化性能。
关键词： 免疫算法； 模糊系统； 径向基神经网络； 软测量
引用格式：MENG Ke, DONG Zhao-yang, GAO Xiao-dan, et al. A fuzzy immune algorithm and its application in solvent tower soft sensor modeling. Journal of Measurement Science and Instrumentation, 2015, 6(2)： 197-204. ［doi： 10.3969／j.issn.1674-8042.2015.02.016］
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