上海化工
上海化工
상해화공
SHANGHAI CHEMICAL INDUSTRY
2012年
11期
13-17
,共5页
乙烯%裂解%支持向量机%计划%优化
乙烯%裂解%支持嚮量機%計劃%優化
을희%렬해%지지향량궤%계화%우화
Ethylene%Cracking%Support vector machine%Plan%Opimization
采用支持向量机（SVM）、粒子群搜索最优算法实现烯烃裂解原料结构的优化选择，相比以往原料优选方法，该方法建模与维护便捷、计算精度高，达到根据市场价格变化及时调整生产运行过程中烯烃裂解原料结构的目的，在竞争日益激烈的市场环境下，能提升烯烃裂解生产过程的产出效益。
採用支持嚮量機（SVM）、粒子群搜索最優算法實現烯烴裂解原料結構的優化選擇，相比以往原料優選方法，該方法建模與維護便捷、計算精度高，達到根據市場價格變化及時調整生產運行過程中烯烴裂解原料結構的目的，在競爭日益激烈的市場環境下，能提升烯烴裂解生產過程的產齣效益。
채용지지향량궤（SVM）、입자군수색최우산법실현희경렬해원료결구적우화선택，상비이왕원료우선방법，해방법건모여유호편첩、계산정도고，체도근거시장개격변화급시조정생산운행과정중희경렬해원료결구적목적，재경쟁일익격렬적시장배경하，능제승희경렬해생산과정적산출효익。
Support vector machine and particle swarm search optimal algorithm are used to achieve the optimal selection of olefin cracking feedstock. In contrast with the previous methods of optimizing the composition of feedstock, the method presented in this paper provides a easy way for modeling and convenient maintenance with high accuracy, and it could obtains the goal to adjust the composition of feedstock according to market price changes timely during the production process. Accordingly, it also could enhances the output efficiency of the olefin cracking process in the increasingly competitive market environment.
