City and State Weather Forecasting Through Mutual ANN and HMM Integration

Authors

  • Mr. Rama Nandan Tripathi, Parimal Tiwari, Shalini Bajpai, Rushda khatoon, Harshita Srivastava,Shaziya Hussain

DOI:

https://doi.org/10.48047/resmil.v13i4.4537

Keywords:

Hybrid Markov model, artificial neural network, training and testing data, regression analysis, Matlab, weather prediction, accurate result

Abstract

This paper shows a strategy to conjecture and settles on a choice of weather condition. In the majority of the urban communities around the globe, individuals attempt to settle on relaxation exercises on their extra time however climate condition would not be appropriate for them. Since the climate conditions in India are flighty, a methodology must be created to gauge climate effectively. By gauging climate definitely, we can anticipate and beat numerous dangers that could prompt extraordinary misfortune to a country. Thus, so as to do this, the Hidden Markov Model and Artificial Neural Network has been deciding for shared cooperation of two states to foresee the climate condition and as yield third states are been predicated. Altogether, to the train, the model and likelihood of an event of an occasion are determined by watching climate information for the most recent 21 years. Because of which the model will anticipate the future five years of information. We will likely enjoy the exact climate.

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Published

2023-12-20

How to Cite

Mr. Rama Nandan Tripathi, Parimal Tiwari, Shalini Bajpai, Rushda khatoon, Harshita Srivastava,Shaziya Hussain. (2023). City and State Weather Forecasting Through Mutual ANN and HMM Integration. RES MILITARIS, 13(4), 907–916. https://doi.org/10.48047/resmil.v13i4.4537