Predictive Modeling of Weather Parameters by Artificial Neural Network Approach

The artificial neural network (aNNs) is becoming increasingly common in the analysis of hydrology, water resources and atmospheric problem. An ANN is a massive parallel-distributed processor that has a natural propensity for storing the experimental knowledge and making it available for further use. Neural networks essentially involve a nonlinear modelling approach that provides a fairly accurate universal approximation to any function. In this research an artificial Neural Network model was developed for ten years (2006–2015) weather parameters and used to observe the behaviour and flow of all weather parameter at the Water and Land management Institute (WaLmI), aurangabad (mH) region. It was found that the neural network model consistently gives superior prediction as compare to other prediction techniques likes moving average, exponential smoothing, Autoregressive moving average model etc. Based on the result of this study, artificial neural network modeling appears to be a promising technique for the prediction of variation and flow of all weather parameter for aurangabad region.