Abstract
Forecasting of future rainfall from previous years data samples has always challenging and major area to focus. There are various factors are applied to anticipate the rainfall such as Mean sea-level, temperature, pressure, wind speed, humidity, etc. We have inaugurated a strategy for predicting the average ground rainfall over the districts of Karnataka state from the past rainfall data applying modified ANN approach without conceiving the rainfall parameters, but considering the average rainfall rates of the previous years and primarily focus on optimization techniques to reduce the error rate during training process. The proposed approach predicts the average rainfall of next consequent year, on inputting anyone year’s rainfall data of any districts taken into account. The suggested technique is implemented in MATLAB and the results are tested.
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Acknowledgements
We would like to thank Ms. Shalini Deepak, Agriculture Officer, Bangalore, India, Karnataka State Natural Disaster Monitoring Centre, Bangalore, Dr. K. C. Gouda, Senior Scientist, CSIR-CMMACS, Bangalore, India and Linyi Top Network Pvt. Ltd, Shandong province, Linyi, China.
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Naveen, L., Mohan, H.S. (2019). High-Resolution Weather Prediction Using Modified Neural Network Approach Over the Districts of Karnataka State. In: Smys, S., Bestak, R., Chen, JZ., Kotuliak, I. (eds) International Conference on Computer Networks and Communication Technologies. Lecture Notes on Data Engineering and Communications Technologies, vol 15. Springer, Singapore. https://doi.org/10.1007/978-981-10-8681-6_14
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DOI: https://doi.org/10.1007/978-981-10-8681-6_14
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