A319合金固溶工艺建模与遗传优化  

Modeling and Optimization of Solution -Heat-Treated A319 Alloy with Adaptive Neuro-Fuzzy Inference System and Genetic Algorithms

作　　者：黄小叶[1] 董杰[1] 夏伯才[1] 

机构地区：[1]中国工程物理研究院工学院,四川绵阳621900

出　　处：《教学与科技》2009年第2期1-9,共9页Teaching and Science Technology

基　　金：论文受中国工程物理研究院科学技术基金项目（编号：20040660及20000329）资助.

摘　　要：综合自适应模糊推理的建模功能和神经网络的学习能力，采用自适应模糊推理方法，直接从实验数据中提取规则，建立A319合金固溶处理工艺模型，获得工艺规律。以质量指标为目标函数，用遗传算法优化工艺参数，达到强度和韧性的良好配合。By the coupling of adaptive fuzzy inference modeling and artificial neural network learning ability, an adaptive neuro-fuzzy inference system, which could better model the solution treatment process of A319 Alloy, has been developed directly from the experimental data. Cast alloy quality index is used as object function to determine optimal solution temperature and time by integrating in the genetic optimization procedure.

关 键 词：A319 固溶处理 自适应模糊推理 遗传算法 

分 类 号：O242.23[理学—计算数学] TP391.73[理学—数学]