MODELLING AND PREDICTION OF WATER CURRENT USING ARTIFICIAL NEURAL NETWORKS: A CASE STUDY OF THE COMMODORE CHANNEL

Authors

  • OT Badejo DEPT OF SURVEYING AND GEOINFORMATICS, UNIV. OF LAGOS, AKOKA YABA, LAGOS STATE, NIGERIA
  • OT Jegede DEPARTMENT OF SURVEYING AND GEOINFORMATICS, UNIVERSITY OF LAGOS, LAGOS STATE, NIGERIA
  • HO Kayode DEPARTMENT OF SURVEYING AND GEOINFORMATICS, UNIVERSITY OF LAGOS, LAGOS STATE, NIGERIA
  • OO Durudola DEPT OF SURVEYING AND GEOINFORMATICS, UNIV. OF LAGOS, AKOKA YABA, LAGOS STATE, NIGERIA
  • SO Akintoye DEPARTMENT OF SURVEYING AND GEOINFORMATICS, UNIVERSITY OF LAGOS, LAGOS STATE, NIGERIA

Keywords:

Artificial Neural Network, Commodore Channel, Coastal Inlet, Water Current, Back Propagation.

Abstract

Water current modelling and prediction techniques along coastal inlets have attracted growing concern in recent years. This is largely so because water current component continues to be a major contributor to movement of sediments, tracers and pollutants, and to a whole range of offshore applications in engineering, environmental observations, exploration and oceanography. However, most research works are lacking adequate methods for developing precise prediction models along the commodore channel in Lagos State. This research work presents water current prediction using Artificial Neural Networks (ANNs). The Back Propagation (BP) technique with feed forward architecture and optimized training algorithm known as Levenbergq-Marquardt was used to develop a Neural Network Water Current Prediction model-(NNWLM) in a MATLAB programming environment. It was passed through model sensitivity analysis and afterwards tested with data from the Commodore channel (Lagos Lagoon). The result revealed prediction accuracy ranging from 0.012 to 0.045 in terms of Mean Square Error (MSE) and 0.80 to 0.83 in terms of correlation coefficient (R-value). With this high performance, the Neural network developed in this work can be used as a veritable tool for water current prediction along the Commodore channel and in extension a wide variety of coastal engineering and development, covering sediment management program: dredging, sand bypassing, beach-contingency plans, and protection of beaches vulnerable to storm erosion and monitoring and prediction of long-term water current variations in coastal inlets.

 

http://dx.doi.org/10.4314/njt.v39i3.37

Published

2020-06-22

Issue

Section

Agricultural, Bioresources, Biomedical, Food, Environmental & Water Resources Engineering