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Neuro-Knowledge-Based Expert System (NKBES) for Optimal Scheming of Die Casting Process
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作者 QiaodanHU PengLUO +1 位作者 YiYANG LiliangCHEN 《Journal of Materials Science & Technology》 SCIE EI CAS CSCD 2004年第5期622-626,共5页
We develop a neuro-knowledge-based expert system (NKBES) frame in this work. The system mainly concerns with decision of gating system and die casting machine based on a neuro-inference engine launched under the MATLA... We develop a neuro-knowledge-based expert system (NKBES) frame in this work. The system mainly concerns with decision of gating system and die casting machine based on a neuro-inference engine launched under the MATLAB software environment. For enhancement of reasoning agility, an error back-propagation neural network was applied. A rapidly convergent adaptive learning rate (ALR) and a momentum-based error back-propagation algorithm was used to conduct neuro-reasoning. The working effect of the system was compared to a conventional expert system that is based on a two-way (forward and backward) chaining inference mechanism. As the reference, the present paper provided the neural networks sum-squared error (S5E) and ALR vs iterative epoch curves of process planning case mentioned above. The study suggests that the neuro-modeling optimization application to die casting process design has good feasibility, and based on that a novel and effective intelligent expert system can be launched at low cost. 展开更多
关键词 Die casting neuro-knowledge-based expert system Process planning
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