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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Dibo Hou Zekui Zhou |
| Copyright Year | 2005 |
| Description | Author affiliation: Dept. of Control Sci. & Eng., Zhejiang Univ., Hangzhou (Dibo Hou; Zekui Zhou) |
| Abstract | For on-line measuring the periodic fouling resistance in recipe alternation, a novel soft-sensing approach based on FNN (fuzzy neural network), FCM (fuzzy c-means clustering) and OED (orthogonal experimental design) was investigated. The periodic fouling resistance is modeled by two parts: the increase of short-term fouling in one batch and the long-term irreversible fouling at the beginning of the batch. FCM algorithm was used to cluster all the recipes into classes, and give each recipe a fuzzy membership belongs to one class. Based on the membership matrix, a FCM neuron was designed and accordingly a hybrid FNN that is robust to recipe alternation was proposed. OED were used to select out the key parameters influencing the long-term fouling and short-term fouling respectively. Two hybrid FNN networks are trained to learn the formation trends of the short-term fouling and long-term fouling trend. The new measurement scheme combines the advantages of FCM, OED and FNN, have a good performance to predict the fouling in recipe alternation. The experimental results and the comparison to other methods show the new scheme is effective |
| Starting Page | 1280 |
| Ending Page | 1285 |
| File Size | 259486 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780392981 |
| DOI | 10.1109/ICSMC.2005.1571323 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2005-10-12 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Fuzzy neural networks Neural networks Fuzzy control Electrical resistance measurement Design engineering Helium Artificial neural networks Surface resistance Organic materials Design for experiments FCM Fouling recipe FNN |
| Content Type | Text |
| Resource Type | Article |
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