Fuzzy Logic Approach to Predicting Rainfall Patterns

Rainfall prediction is of paramount importance for a wide range of applications, including agriculture, water resource management, and disaster preparedness. Traditional numerical models, while effective, still face challenges hindering the accuracy, accessibility, and effectiveness of rainfall pred...

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Bibliographic Details
Main Authors: Seeboruth, Keshika, Wen, Lai Zhi, Hameed, Vazeerudeen Abdul, Ling, Tan Yee, Rajadorai, Kesava Pillai, Rana, Muhammad Ehsan
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Atmospheric modeling
Computational modeling
Fuzzy logic
Mamdani model
membership functions
prediction model
Rain
soft computing
Weather forecasting
Wind speed
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Summary:Rainfall prediction is of paramount importance for a wide range of applications, including agriculture, water resource management, and disaster preparedness. Traditional numerical models, while effective, still face challenges hindering the accuracy, accessibility, and effectiveness of rainfall predictions. As such, this study aims at developing a simple model for rainfall prediction in New Delhi, India using Mamdani fuzzy inference system. The meteorological parameters considered for rainfall modeling in this study encompass temperature, atmospheric pressure, humidity levels, dew point, and wind speed. The dataset used in this study is from the Delhi Weather Data dataset. The model was able to achieve an accuracy of 63.29%, precision of 62.44%, recall of 66.7% and F1 score of 64.49%.
ISSN:2643-2447
DOI:10.1109/SCOReD60679.2023.10563899