本文關(guān)鍵詞：基于神經(jīng)網(wǎng)絡專家系統(tǒng)的工藝推理研究——以軸類零件為例　出處：《現(xiàn)代制造工程》2017年09期 　論文類型：期刊論文

  更多相關(guān)文章： 工藝推理 專家系統(tǒng) 神經(jīng)網(wǎng)絡 特征矩陣

【摘要】：目前,傳統(tǒng)專家系統(tǒng)工藝推理時存在零件信息提取不完整、知識獲取困難和推理能力弱的問題,采用基于神經(jīng)網(wǎng)絡和規(guī)則的混合推理機制替代傳統(tǒng)專家系統(tǒng)可以解決有效上述問題。首先,運用特征技術(shù)提取零件信息,將零件信息轉(zhuǎn)換為特征矩陣,作為神經(jīng)網(wǎng)絡專家系統(tǒng)的輸入;然后,根據(jù)特征矩陣搜索推理策略,基于軸類零件特征將神經(jīng)網(wǎng)絡分為精度、形狀和熱處理三類子網(wǎng)絡,采用動量-自適應學習率BP算法訓練網(wǎng)絡;最后設計與實現(xiàn)了混合系統(tǒng)工藝推理過程。
[Abstract]:At present, there are some problems in the traditional expert system, such as incomplete information extraction, difficult knowledge acquisition and weak reasoning ability. Using hybrid reasoning mechanism based on neural network and rules to replace the traditional expert system can effectively solve the above problems. Firstly, the feature technology is used to extract part information and convert part information into feature matrix. As the input of neural network expert system; Then, according to the feature matrix search and reasoning strategy, the neural network is divided into three subnetworks: precision, shape and heat treatment based on the feature of shaft parts, and the momentum adaptive learning rate BP algorithm is used to train the network. Finally, the process of process reasoning in hybrid system is designed and implemented.
【作者單位】： 燕山大學經(jīng)濟管理學院;北京航空航天大學;遷安市九江線材有限責任公司;
【分類號】：TH16;TP18
【正文快照】： 3遷安市九江線材有限責任公司,唐山064400)0引言自20世紀60年代末CAPP系統(tǒng)誕生以來,一直受到國內(nèi)外學者的重視,先后提出派生式、創(chuàng)成式、交互式等CAPP系統(tǒng)[1],而零件信息提取和工藝推理方法一直是研究的重點和難點。零件信息提取作為專家系統(tǒng)推理的前提和基礎,至今仍然存在零，

本文編號：1414739