Paper Title :Designing & Comparison of Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System for Line Following Robot

Author :Pankti Bhatt, Jeegar Trivedi

Article Citation :Pankti Bhatt ,Jeegar Trivedi , (2021 ) " Designing & Comparison of Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System for Line Following Robot " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 1-5, Volume-9,Issue-12

Abstract : This paper presents designing &comparative study of simulation results ofArtificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) for Line Following Robot. In this study, ANN was assessed with 3 neurons in the input layer, one hidden layer with 8 neurons, and 2 neurons in the output layer. The inputs are left IR sensor, Middle IR sensor & Right IR sensor in ANN and ANFIS and the outputs are left motor and right motor in ANN and one output as direction in ANFIS. The mean square error was calculated with ANN & ANFIS and ANFIS was found to show the minimum error rate with respect to ANN. Thus, in this study, ANFIS is considered to be the best model for line following robot. Keywords - ANFIS, ANN, Line following Robot, LFR, Mean Square Error.

Type : Research paper

Published : Volume-9,Issue-12

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