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人工神经网络在不锈钢-铝固液相压力复合研究中的应用
ARTIFICIAL NEURAL NETWORKS APPLIED TO INVESTIGATION ON SOLID-LIQUID PRESSURE BONDING OF STAINLESS STEEL AND ALUMINIUM
【摘要】 采用人工神经网络方法研究了助焊剂浓度、铝液温度、模具温度及压力与不锈钢-铝固液相压力复合剪切强度间的力学关系,并结合遗传算法优化出了最佳复合工艺.
【Abstract】 Effects of concentration of flux solution,temperature of liquid aluminium,temperature of tools and pressure on shearing strength in solid-liquid pressure bonding of stainless steel and aluminium were investigated by means of artificial neural networks. The optimum bonding parameters were optimized with a genetic algorithm.
【关键词】 人工神经网络;
固液相压力复合;
遗传算法;
【Key words】 artificial neural network; solid-liquid pressure bonding; genetic algorithm;
【Key words】 artificial neural network; solid-liquid pressure bonding; genetic algorithm;
【基金】 辽宁省科委重点资助
- 【文献出处】 金属学报 ,ACTA METALLRUGICA SINICA , 编辑部邮箱 ,1996年12期
- 【分类号】TB331
- 【被引频次】12
- 【下载频次】53