Optimization of Roll Forming Process Using the Integration Between Genetic Algorithm and Hill Climbing with Neural Network

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| | |Optimization of Roll Forming Process Using The Integration Between Genetic Algorithm and Hill Climbing With Neural Network | | | |Hong-Seok Park and Ta Ngoc Thien Binh# | |School of Mechanical Engineering, Ulsan University, Daehak-ro 93, Nam-gu, Ulsan, South-Korea, 680-749 | |# Corresponding Author / E-mail: thienbinhtme@mail.ulsan.ac.kr, TEL: +82-52-259-1458, FAX: +82-52-259-1680 | | | | | | | |Knowledge-Based Neural Network (KBNN) model is one of the most useful methods which is used to predict every single variability to perform the | |parameters on data of the Roll forming (RF) process. It is true that the quality of product and the parameters in RF process depend on the reliability | |of the training in KBNN. To achieve this, the new novel of the optimal algorithm including integration between Genetic Algorithm (GA) and Hill climbing| |Algorithm (HCB) was proposed to train the KBNN model. Initially, the GA is applied to find the local optimal region, then, the HCB will detect the...
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