(中南工業(yè)大學礦物工程系，長沙 410083；
中國科學院上海冶金研究所， 上海 200050)
摘 要: 以化學鍵參數(shù)作為人工神經(jīng)網(wǎng)絡的輸入，實測相圖數(shù)據(jù)為輸出，將采用誤差反向傳播算法訓練好的神經(jīng)網(wǎng)絡用于對未知相圖作計算機預報，將數(shù)據(jù)庫與知識庫相結(jié)合，設計和開發(fā)出了一個檢索和預報二元及部分三元熔鹽系相圖特征的專家系統(tǒng)。該數(shù)據(jù)庫包括各類已知熔鹽相圖特征的實驗數(shù)據(jù)及熔鹽系各種元素的化學鍵參數(shù)，而知識庫為訓練好的人工神經(jīng)網(wǎng)絡，通過人機對話形式提供相圖特征的各種信息。給出了3個實際應用例子， 對預報結(jié)果進行的實驗驗證表明該專家系統(tǒng)對未知相圖特征的預報是可靠的。
關鍵字: 專家系統(tǒng) 人工神經(jīng)網(wǎng)絡 熔鹽相圖 化學鍵參數(shù)
（Department of Mineral Engineering, Central South University of Technology, Changsha 410083, P. R. China
Shanghai Institute of Metallurgy, Chinese Academy of Sciences, Shanghai 200050, P. R. China）
Abstract:An expert system for retrieval and prediction of the properties in some binary and ternary phase diagrams of molten salt systems has been built. The models obtained by chemical bond parameters-artificial neural network method has been used for computerized prediction. The data base consisting of the known properties of phase diagrams and chemical bond parameters and the knowledge base produced by the trained artificial neural network were included in this expert system. By man-machine interfacing, the formability, chemical stoichiometry, melting type and melting point of the intermediate compound of phase diagram can be retrieved or predicted.
Key words: expert system artificial neural network phase diagram of molten salt chemical bond parameter
