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Title: :  Literature Survey:weather prediction and climate analysis using machine learning
PaperId: :  17553
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 8 Issue 3 2022
DUI:    16.0415/IJARIIE-17553
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
CHRISTINA MARY JOLLYI.E.S COLLEGE OF ENGINEERING
SAFNA K.MI.E.S COLLEGE OF ENGINEERING
Dr. S. Brilly SangeethaI.E.S COLLEGE OF ENGINEERING

Abstract

Computer Engineering
linear regression,machine learning,naive baye's classifier
Weather is an important aspect of a person’s life as it can help us to know when it’ll rain and when it’ll be sunny. Weather forecasting is the attempt by meteorologists to predict the weather conditions at some future time and the weather conditions that may be expected. The climatic condition parameters are based on the temperature, pressure, humidity, dewpoint, rainfall, precipitation, wind speed and size of dataset. Here, the parameters temperature, pressure, humidity, dewpoint, precipitation, rainfall is only considered for experimental analysis. Weather forecasting is simply the prediction of future weather based on different parameters of the past like temperature, humidity, dew, wind speed and direction, precipitation, Haze and contents of air, Solar and terrestrial radiation etc. Weather forecast is an important factor affecting people’s lives. Once the data is taken, it is trained. The heart of this project is the Linear Regression algorithm which is used to predict the weather using these data. The more parameters considered, the higher the accuracy. This project can help many people finding the weather of tomorrow. Prediction requires accurate classification of data .In order to predict the uncertain things, we need to analyse various factors which involved either directly or indirectly. Weather is one of the most influential environmental constraints in every phase of our lives on the earth. So as to make everyday tasks we are very much rely on weather and need to know weather condition on before hands. This could be achieved by predicting the weather condition such as humidity, rainfall, temperature, thunder, fog, etc. This helps us in protecting ourselves from abnormal conditions and avoids unnecessary delays. The main objective of this paper is to design an effective weather prediction model by the use of multivariate regression or multiple linear regressions and support vector machine (SVM). As of now, there are various debates going on around the world either scientifically or non-scientifically regarding the change of Earth's climate in fore coming decades/centuries and what impact it will cause on all the living creatures. Scientific models which predict future climates offer the best plan or aspiration for providing the information which will allow the world's policy maker to take preventive measures and make better decisions for the future of the Earth and for the future lives. This paper explores about weather forecast in effective way.

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IJARIIE CHRISTINA MARY JOLLY, SAFNA K.M, and Dr. S. Brilly Sangeetha. "Literature Survey:weather prediction and climate analysis using machine learning" International Journal Of Advance Research And Innovative Ideas In Education Volume 8 Issue 3 2022 Page 5093-5095
MLA CHRISTINA MARY JOLLY, SAFNA K.M, and Dr. S. Brilly Sangeetha. "Literature Survey:weather prediction and climate analysis using machine learning." International Journal Of Advance Research And Innovative Ideas In Education 8.3(2022) : 5093-5095.
APA CHRISTINA MARY JOLLY, SAFNA K.M, & Dr. S. Brilly Sangeetha. (2022). Literature Survey:weather prediction and climate analysis using machine learning. International Journal Of Advance Research And Innovative Ideas In Education, 8(3), 5093-5095.
Chicago CHRISTINA MARY JOLLY, SAFNA K.M, and Dr. S. Brilly Sangeetha. "Literature Survey:weather prediction and climate analysis using machine learning." International Journal Of Advance Research And Innovative Ideas In Education 8, no. 3 (2022) : 5093-5095.
Oxford CHRISTINA MARY JOLLY, SAFNA K.M, and Dr. S. Brilly Sangeetha. 'Literature Survey:weather prediction and climate analysis using machine learning', International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, 2022, p. 5093-5095. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Literature_Survey_weather_prediction_and_climate_analysis_using_machine_learning_ijariie17553.pdf (Accessed : ).
Harvard CHRISTINA MARY JOLLY, SAFNA K.M, and Dr. S. Brilly Sangeetha. (2022) 'Literature Survey:weather prediction and climate analysis using machine learning', International Journal Of Advance Research And Innovative Ideas In Education, 8(3), pp. 5093-5095IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Literature_Survey_weather_prediction_and_climate_analysis_using_machine_learning_ijariie17553.pdf (Accessed : )
IEEE CHRISTINA MARY JOLLY, SAFNA K.M, and Dr. S. Brilly Sangeetha, "Literature Survey:weather prediction and climate analysis using machine learning," International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, pp. 5093-5095, May-Jun 2022. [Online]. Available: https://ijariie.com/AdminUploadPdf/Literature_Survey_weather_prediction_and_climate_analysis_using_machine_learning_ijariie17553.pdf [Accessed : ].
Turabian CHRISTINA MARY JOLLY, SAFNA K.M, and Dr. S. Brilly Sangeetha. "Literature Survey:weather prediction and climate analysis using machine learning." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 8 number 3 ().
Vancouver CHRISTINA MARY JOLLY, SAFNA K.M, and Dr. S. Brilly Sangeetha. Literature Survey:weather prediction and climate analysis using machine learning. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2022 [Cited : ]; 8(3) : 5093-5095. Available from: https://ijariie.com/AdminUploadPdf/Literature_Survey_weather_prediction_and_climate_analysis_using_machine_learning_ijariie17553.pdf
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