Abstract
Prediction as a matter of fact has always been a key area of interest for the researchers. Prediction of anything can be done in an approximate way, and it cannot be made precisely as anything that is yet to happen cannot be predicted precisely. Weather prediction has been amongst the recent developments in the field of predicting the future. Weather is one such natural phenomenon which till date is mostly predicted using highly sophisticated machines that measure the value of past and with the study of that data by humans gives us the future value. In this paper, we would like to make weather prediction a more autonomous thing requiring minimum interference by humans with the use of artificial neural networks (ANN) as well as fuzzy inference systems. Here the ANN is used basically to memorize the past data of the atmosphere while the fuzzy inference engine is used for decision making as to what is the outcome of a particular output given by the ANN. With the combination of ANN and fuzzy, we would be able to mimic the human brain to some extent and that way some of the tasks will be less time-consuming and a lot more economical.
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Ujjwal, Shivam Kukrety, Likhitha Kakinada, Shalini (2021). Wind Power Forecasting Using Artificial Neural Networks (ANN) and Artificial Neuro-fuzzy Inference System (ANFIS). In: Mahapatra, R.P., Panigrahi, B.K., Kaushik, B.K., Roy, S. (eds) Proceedings of 6th International Conference on Recent Trends in Computing. Lecture Notes in Networks and Systems, vol 177. Springer, Singapore. https://doi.org/10.1007/978-981-33-4501-0_49
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