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Aydin Azizi, Ali Vatnakhah, Majid Hashmipour

Aydin Azizi, Ali Vatnakhah, Majid Hashmipour

University of Technology in Oman

Title: Modeling and optimizing mechanical properties of FSW thick pure copper plates utilizing Artificial Intelligent techniques

Biography

Aydin Azizi is a university professor in the German University of Technology, also he is the Research Focal Point of The Research Council of OMAN (TRC). He’s research area is Mechatronics focusing on developing and investigating different Artificial Intelligent Techniques to model, predict and control of nonlinear systems. Aydin holds BSc. MSc and PhD degrees in Mechanical Engineering.

Ali Vatankhah Barenji is a Research Fellow in Eastern Mediterranean University. He’s research area is Manufacturing focusing on Wireless sensor technology and RFID systems. Ali holds BSc. MSc and PhD degrees in Mechanical Engineering.

Majid Hashemipour is a Professor in Eastern Mediterranean University. He’s research area is Manufacturing and Mechatronics. Majid holds BSc. MSc and PhD degrees in Mechanical Engineering.

Abstract

This investigation is undertaken to develop a model to predict the microstructure and mechanical properties of Friction Stir Welded (FSW) thick pure copper plates using Artificial Neural Networks (ANN) and optimize it utilizing Ring Probabilistic Logic Neurons (RPLN) and Genetic Algorithms (GA). This paper introduces Ring Probabilistic Logic Neuron (RPLN) as a time efficient and accurate algorithm to deal with RNP. Performance of the RPLN is compared with evolutionary Genetic Algorithm (GA). The simulation results show that performance of the RPLN algorithm compared to GA’s is more reliable to deal with optimizing problems, and it is capable of achieving a solution in fewer convergence time steps with better.