Abstract
A new approach of intelligent soft computing based on process neural network for variables estimate of process control system was proposed. Process neural network (PNN) is a new type of artificial neural network put forward in recent years. Some algorithms of PNN were discussed, and convergence rate was comparatively low. An improved algorithm for raising training speed based on function orthogonal basis expansion in PNN for soft computing was researched. After increasing the normalizing rule on original algorithm, and introducing function momentum adjustment item and learning rate automatically adjustment method for network weight function, the training time of learning algorithm for PNN was reduced. The fact showed that the stability and training precision was improved with the learning rate automatic adjustment method, and it can also restrain the network falls into local least by introducing momentum adjustment item,and a good result of application in sewage disposal system was represented.
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© 2007 Springer-Verlag Berlin Heidelberg
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Liu, Z., Wang, X., Cui, L. (2007). On Approach of Intelligent Soft Computing for Variables Estimate of Process Control System. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2007. Lecture Notes in Computer Science(), vol 4682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74205-0_135
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DOI: https://doi.org/10.1007/978-3-540-74205-0_135
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74201-2
Online ISBN: 978-3-540-74205-0
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