Non-Linear Autoregressive Dissolved Oxygen Prediction Model for Paddy Irrigation Channel

Abstract

This study has proposed a non-linear autoregressive model to predict one-day ahead dissolved oxygen in paddy field irrigation channel. A 32-day data is obtained from Kampung Padang To’ La in Pasir Mas, Kelantan using off-the shelf water quality parameter sensors. Analysis has revealed no correlation between dissolved oxygen with pH and electrical conductivity. A non-linear autoregressive model is then developed using the dissolved oxygen measurements and artificial neural network. A prediction model developed using Levenberg-Marquardt algorithm yielded the best results with overall regression of 0.9253. The model has also passed all correlation tests and can therefore, be accepted.