Proceedings of the 2022 8th International Conference on Humanities and Social Science Research (ICHSSR 2022)

Rain Prediction Based on Machine Learning

Authors
Ye Zhao1, *, Hanqi Shi2, Yifei Ma3, Mengyan He4, Haotian Deng5, Zhou Tong6
1The University of Ningbo Nottingham, NingBo, 315100, China,scyyz6@nottingham.edu.com
2Dana Hall School, MA, USA,hanqi.shi@danahall.org
3Hunan University, Changsha, China,1250152196@qq.com
4Xi’an Jiaotong University, Xian, China,1913004851@qq.com
5Chongqing BI Academy, Chongqing, 401120, China,1559117929@qq.com
6Xi’an Jiaotong-Liverpool University, Jiangsu, China
*Correspondence author: scyyz6@nottingham.edu.com
Corresponding Author
Ye Zhao
Available Online 1 June 2022.
DOI
10.2991/assehr.k.220504.536How to use a DOI?
Keywords
machine learning; Rain prediction; LSTM
Abstract

Our purpose is to try to use machine learning algorithms to predict the weather of the next day, since whether it will rain tomorrow is a very important indicator of the weather. In order to find the most predictable attributes of rain, The researcher use line charts, matrix graphs, and scatterplot graphs for visualization and analysis. The researcher find that several pairs of attributes have a high degree of similarity and correlation. In the fitting stage, the researcher used simple models such as KNN, decision tree, and ridge regression to evaluate its basic prediction quality and found that the accuracy rate is around 0.78. Since in the visualization stage, the researcher found that the samples that rained today have a slightly higher probability of raining the next day, the researcher tried to use LSTM to analyze the impact of historical weather and found that the relationship is not strong. Finally, logistic regression turns out to have the highest accuracy of 0.85, followed by adaboost with an accuracy of 0.82. Whether it will rain remains unpredictable to some extent.

Copyright
© 2022 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license.

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Volume Title
Proceedings of the 2022 8th International Conference on Humanities and Social Science Research (ICHSSR 2022)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
1 June 2022
ISBN
10.2991/assehr.k.220504.536
ISSN
2352-5398
DOI
10.2991/assehr.k.220504.536How to use a DOI?
Copyright
© 2022 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license.

Cite this article

TY  - CONF
AU  - Ye Zhao
AU  - Hanqi Shi
AU  - Yifei Ma
AU  - Mengyan He
AU  - Haotian Deng
AU  - Zhou Tong
PY  - 2022
DA  - 2022/06/01
TI  - Rain Prediction Based on Machine Learning
BT  - Proceedings of the 2022 8th International Conference on Humanities and Social Science Research (ICHSSR 2022)
PB  - Atlantis Press
SP  - 2957
EP  - 2970
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.220504.536
DO  - 10.2991/assehr.k.220504.536
ID  - Zhao2022
ER  -