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Weather Prediction using Scikit-Learn

Sudhnya Kashikar1 , Sumedha Patil2 , Ameya Vedantwar3 , Shivani Katpatal4 , Sofia Pillai5

Section:Review Paper, Product Type: Journal Paper
Volume-7 , Issue-4 , Page no. 36-40, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i4.3640

Online published on Apr 30, 2019

Copyright © Sudhnya Kashikar, Sumedha Patil, Ameya Vedantwar, Shivani Katpatal, Sofia Pillai . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Sudhnya Kashikar, Sumedha Patil, Ameya Vedantwar, Shivani Katpatal, Sofia Pillai, “Weather Prediction using Scikit-Learn,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.36-40, 2019.

MLA Style Citation: Sudhnya Kashikar, Sumedha Patil, Ameya Vedantwar, Shivani Katpatal, Sofia Pillai "Weather Prediction using Scikit-Learn." International Journal of Computer Sciences and Engineering 7.4 (2019): 36-40.

APA Style Citation: Sudhnya Kashikar, Sumedha Patil, Ameya Vedantwar, Shivani Katpatal, Sofia Pillai, (2019). Weather Prediction using Scikit-Learn. International Journal of Computer Sciences and Engineering, 7(4), 36-40.

BibTex Style Citation:
@article{Kashikar_2019,
author = {Sudhnya Kashikar, Sumedha Patil, Ameya Vedantwar, Shivani Katpatal, Sofia Pillai},
title = {Weather Prediction using Scikit-Learn},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {7},
Issue = {4},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {36-40},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3990},
doi = {https://doi.org/10.26438/ijcse/v7i4.3640}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i4.3640}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3990
TI - Weather Prediction using Scikit-Learn
T2 - International Journal of Computer Sciences and Engineering
AU - Sudhnya Kashikar, Sumedha Patil, Ameya Vedantwar, Shivani Katpatal, Sofia Pillai
PY - 2019
DA - 2019/04/30
PB - IJCSE, Indore, INDIA
SP - 36-40
IS - 4
VL - 7
SN - 2347-2693
ER -

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Abstract

Weather is the most important factor in terms of farming and agriculture. It continuous, data-intensive, multidimensional, and chaotic process. These properties of weather make its forecasting a formidable challenge. The most technologically challenged problems of the last century are weather forecasting. The harvest of crops is dependent on this factor. To make an accurate weather prediction is one of the major challenges that is being faced all over the world. Scientists have tried their best to forecast environmental characteristics using a number of methods and some of these methods are more accurate than others. Weather forecasts provide critical information about future weather. Every year notorious weather harms the life, property and many government activities which is usually heavily funded is destroyed, as a result weather forecasting would help government to plan out things in advance to prepare its citizens for the worst of the weather. There are many different methodologies that have come into observation regarding weather prediction. This paper describes one of the many techniques used for prediction of weather which will be beneficial for the farmers, agricultural and scientists. It will help them to better understand the weather for yielding crops and for studying environment too.

Key-Words / Index Term

Regression, Pandas, Scikit Learn, Numpy

References

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