AN INTELLIGENT SOFT MEASUREMENT METHOD FOR PREDICTING PARAMETERS

摘要

An intelligent soft measurement and information processing method for predicting parameters of process control system was proposed. Process neural network (PNN) is a new configuration of artificial neural network put forward in recent years. Some algorithms of PNN were discussed, and these algorithms were based on function orthogonal basis expansion, yet the convergence rate was comparatively low. An improved algorithm for raising training speed based on function orthogonal basis expansion in PNN for soft measurement was researched. After increasing the normalizing rule on the 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, and a good result was represented by simulation in wastewater treatment system.