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題名 | 模糊類神經網路學習演算法之推導與應用--以鋪面診斷為例=Development and Applications of Learning Algorithm for Fuzzy Neural Networks: A Case of Pavement Diagnosis |
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作者姓名(中文) | 邱裕鈞; 藍武王; | 書刊名 | 運輸計劃 |
卷期 | 26:2 1997.06[民86.06] |
頁次 | 頁233-252 |
分類號 | 442.15 |
關鍵詞 | 模糊類神經網路; 模糊集合; 類神經網路; 鋪面診斷; Fuzzy neural networks; Fuzzy sets; Neural networks; Pavement diagnosis; |
語文 | 中文(Chinese) |
中文摘要 | 模糊類神經網路係整合模糊集合處理人類認知過程之不確定性及類神經網路之強大 學習能力與適應能力而成,更接近人類接受訊息、處理資料與輸出訊息之型式,已證明具備論 域近似之功能。本文利用α-cuts技術進行模化,並提出具體可行之學習演算法。最後應用於 鋪面診斷專家系統,結果顯示本演算法之準確度高達96%(學習資料)及85%(驗證資料 )。敏感度分析結果亦顯示本演算法於大部分狀況下均十分精確有效。 |
英文摘要 | Fuzzy sets can deal with the uncertainties within the process of human recognition; while neural networks have powerful learning and adaptive capabilities. Fuzzy neural networks(FNN)which integrate the fuzzy sets and the neural networks are more similar to the human way of recognizing, processing and outputting information and are proved to be universal approximators. In this paper, we model the FNN by the α-cuts techniques and develop a learning algorithm. To demonstrate the applicability of this algorithm, an expert system for pavement diagnosis is tested. It is found that the correct rates for the learning patterns and validation patterns are 96% and 85% respectively. The sensitivity analysis also shows that this learning algorithm performs quite well in most situations. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。