Selection of optimal material and operating conditions in composite manufacturing . Part I : computational tool
نویسندگان
چکیده
The Genetically Optimized Neural Network System (GONNS) is proposed as a human-like decision-making tool for the selection of optimum composite material and operating conditions. Multiple neural networks represent the characteristics of the system after a training process and genetic algorithms find the optimum operating conditions. The error of the GONNS was found to be less than 1% when the neural networks-represented analytical functions and genetic algorithms were used to select the optimal conditions. The GONNS is very promising for many complex optimization problems when analytical equations are not available to represent the characteristics of the system.
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