A Supervised Fuzzy ART Neural Network for Pattern Classification
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摘要: 探討了一種將有監督學習機制融合到模糊ART網絡構成一個有監督的模糊ART神經網絡模型.這種網絡能同時處理有監督和無監督學習問題,并具有積累和增加網絡學習的能力.對該網絡進行了滾動軸承檢測數據模式分類實驗,并與BP網絡進行了比較性實驗.結果表明:該網絡具有良好模式分類能力和較好的可塑性.Abstract: A new neural network model that incorporates a supervised mechanism into a fuzzy ART is investigated. The model can cope with supervised learning and unsupervised learning simultaneously, and has the ability of incremental learning. A few experiments of bearing pattern classification prove pefformance of the model and by comparing pefformance of the model with BP model. The results of experiments indicate tha the model has the ability of pattem classification and flexibility.
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Key words:
- neural network /
- fuzzy theory /
- pattern recognition
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