Abstract
Artificial neural networks have wide range of application, one of which is time series prediction. This paper represents a case study on time series prediction as an application of neural networks. The case study was done for the rainfall prediction using the local database in India. The results were obtained by the comparative study of neural network architectures like back propagation (BPNN), generalized regression (GRNN), and radial basis function (RBFNN).
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Sardeshpande, K.D., Thool, V.R. (2019). Rainfall Prediction: A Comparative Study of Neural Network Architectures. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 755. Springer, Singapore. https://doi.org/10.1007/978-981-13-1951-8_3
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DOI: https://doi.org/10.1007/978-981-13-1951-8_3
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