Mean sea level modelling using the neural network along the Chennai coast

Abstract This study focuses on the trend analysis of sea level data along Chennai coast and thereby checks structural change in dataset using Chow method. also proposed a methodology for predicting mean with feed-forward neural network (FFNN) wavelet transform (WTNN) models. The shows that breakpoint is observed year 1994 found an overall increasing during selected time period at coast. For model development, better understanding influencing parameters essential. Hence, correlation analyses have been performed wind speed, surface salinity, pressure are variables modelling data. Apparently, these considered as potential inputs development. To compare performance all developed models, Root Mean Square Error, Correlation Coefficient, Nash–Sutcliffe Efficiency (NSE) were utilized. results indices graphical indicators show WTNN Model 4 outperformed other It was noticed percentage increase efficiency NSE 29.52% compared to