Over the past few decades, weather forecasting has grown in importance as a research area but the traditional methods are still not forecasting the weather conditions accurately. It is now one such domain that attracted many researchers because it is well connected with the human life. In this research study, several weather constraints were collected from open access platform and using linear regression (LR) and deep neural network (DNN), the model is trained for different combinations. The dataset was taken from Kaggle (an online platform for public data). The results achieved using this model are compared and analyzed through mean absolute error and median absolute error between actual and predicted values.


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    Titel :

    Analysis of Weather Forecasting and Prediction Using Neural Networks


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Sharma, Sanjay (Herausgeber:in) / Subudhi, Bidyadhar (Herausgeber:in) / Sahu, Umesh Kumar (Herausgeber:in) / Choubisa, Manish (Autor:in) / Dubey, Manish (Autor:in) / Yadav, Surendra Kumar (Autor:in) / Virwani, Harshita (Autor:in)

    Kongress:

    International Conference on Robotics, Control, Automation and Artificial Intelligence ; 2022 November 24, 2022 - November 26, 2022



    Erscheinungsdatum :

    2023-11-18


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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