Predictive model of parameters validation for the Vortexanda technique by using fuzzy logic and neural network

• Published in: Journal of Mechanical Engineering
• Main Author: Kamal N.A.; Shin S.; Park H.
• Format: Article
• Language: English
• Published: UiTM Press 2017
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042081969&partnerID=40&md5=5de9835543223f9b944eb85bb29efed4

This study used fuzzy and neural network models for validating the non-dimensional parameters of experimental findings from development of vortexanda technique in the urban small hydropower system. Fuzzy and neural network was selected due to the significant contribution in verifying or predicting the parameters especially for the non-linear process. The aim of this study was to establish a validation model to verify the accuracy of non-dimensional parameters in predicting the removal efficiency of the vortexanda technique. The result show both models of Neural Network and ANFIS may become as the satisfactory tools in validating the 4 non-dimensional parameters for predicting the removal efficiency in vortexanda system by achieving only minimal error in validating process. The predictive model will help the decision maker to design the vortexanda system based on the suitable value of non dimensional parameters and removal efficiency estimation. This model could be an easier and interactive approach for the decision maker compared to the conventional method. © 2017 Faculty of Mechanical Engineering.