Abstract：At present, the planners can only arrange autoclave continuously according to the curing parameters of relevant process documents and historical data of the curing period, causing planners failure to make a detailed production scheduling plan. Now, data mining algorithm hasn’t been used to predict the curing period of autoclave. To solve the curing time of the autoclave, support vector regression（SVA） method and K–nearest neighbor （KNN） method are used to calculate. The proposed SVR and KNN comparative experiments are performed. Experimental results show that 90% of KNN prediction result is better than support vector regression prediction method, and 90% of the error is less than 0.5 hours. Meanwhile, the reasons for the prediction results of two methods are analyzed.
魏士鹏，王宁，袁喆. 基于数据挖掘算法的热压罐固化周期预测研究[J]. 航空制造技术, 2021, 64(5): 98-102.
WEI Shipeng, WANG Ning, YUAN Zhe. Period Prediction of Autoclave Curing Based on Data Mining Algorithm. Aeronautical Manufacturing Technology, 2021, 64(5): 98-102.
2021, 
