DESIGN AND DEVELOPMENT OF NEURAL NETWORK SIMULATOR

Mohd Helmy Abd Wahab; Ayob Johari; Tg. Halim Tg. Othman; Hafizul Fahri Hanafi; Asma Hanee Ariffin

doi:10.53840/myjict1-1-75

Authors

Mohd Helmy Abd Wahab Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia P.O. Box 101, Parit Raja, 86400 Batu Pahat, Johor
Ayob Johari Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia P.O. Box 101, Parit Raja, 86400 Batu Pahat, Johor
Tg. Halim Tg. Othman TMNet Sdn. Bhd. No. 138C, Ground Floor, Wisma Sentosa, Jalan Sultan Zainal Abidin, 20000 Kuala Terengganu, Terengganu
Hafizul Fahri Hanafi Faculty of Art, Computing and Creative Industry Universiti Perguruan Sultan Idris Tanjung Malim, Perak
Asma Hanee Ariffin Faculty of Art, Computing and Creative Industry Universiti Perguruan Sultan Idris Tanjung Malim, Perak

DOI:

https://doi.org/10.53840/myjict1-1-75

Keywords:

Neural network simulator, logic gate, backpropagation algorithm

Abstract

Neural Networks (NN) are computational models with the capacity to learn, to generalize, or to organize data based on parallel processing. Among all kinds of networks, the most widely used are multi-layer feed-forward Neural Networks that are capable of representing non-linear functional mappings between inputs and outputs and are hailed as “Universal Approximators”. These networks can be trained with a powerful and computationally efficient method called error backpropagation. This paper presents the development of Neural NetworkSimulator using Backpropagation algorithm using Visual Basic 6.0. The methodology used in this development is System Development that consists of five phases. The phases include Preliminary Study, Analysis, Design, Implementation and Maintenance. Testing has been made on logic gate data AND, OR and XOR. Results show that the Neural Networks is 99% accurate.

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