Abstract

Weather forecasting is the utilization of science and innovation to foresee the condition of weather for a specific area. Here this framework will anticipate the climate-dependent on boundaries like temperature, humidity and wind. This framework is a web application with a powerful graphical UI. To foresee the future's climate condition, should use the shift in the states in previous years. The likelihood that it will coordinate inside the range of pioneer days of the last year is exceptionally high. We have proposed using Naive Bayes and K-medoids prediction for climate measure framework with boundaries like temperature, dampness, and wind. It will gauge climate dependent on the record; accordingly, this forecast will demonstrate high accuracy. This framework can be utilized in Navy, Marine, Air Traffic Control, Forestry, Agriculture and Military etc.

References

1. Piyush Kapoor and Sarabjeet Singh Bedi, Weather Forecasting Using Sliding Window Algorithm, ISRN Signal Processing Volume 2013, Article ID 156540.
2. Jose L. Aznarte and Nils Siebert, Dynamic Line Rating Using Numerical Weather Predictions and Machine Learning: a Case Study, IEEE Transactions on Power Delivery ( Volume: PP, Issue: 99 ).
3. Deepti Gupta and Udayan Ghose, A Comparative Study of Classification Algorithms for Forecasting Rainfall, IEEE 978-1-4673-7231-2, ©IEEE Publications 2015.
4. Mohsen Hayati & Zahra Mohebi, Temperature Forecasting Based on Neural Network Approch, WorldApplied Science Journal 2(6) 613-620, 2007, ISSN 818-4952 ©IDOSI Publications 2007.
5. S.S. De, University of Kolkata, Artificial Neural Network Based Prediction of Max. & Min.Temperature in the Summer-Monsoon month over India, Applied Physics Research,Vol.1,No.2,Nov-2009.

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