Application of neural network in prediction of temperature: a review

Abstract

The aim of this study was to review different literatures to assess the applicability of artificial neural network in predicting temperature. Temperature prediction as part of weather prediction involves the application of science and technology to predict the state of temperature for a future period in a specific location. Artificial neural network (ANN) has been found to be a promising tool to be used in temperature prediction because it is able to handle complex and nonlinear physical variables of the atmosphere. The use of ANN for prediction of weather elements has shown significant improvements in prediction and accuracy. The performance of the ANN model varies depending on the nature and number of input data used in training the network, the number of neurons in the hidden layer, architecture of a network, transfer function and on the training algorithms. The choice of ANN architecture and the type of data depend on the nature of the problem to be addressed. ANN is therefore found to be a powerful tool in predicting temperature of a specific place, provided input parameters of the model are well chosen.