ItemConference Paper

AI-Driven Time Series Models for Rainfall Prediction: A Machine Learning Approach

Title
AI-Driven Time Series Models for Rainfall Prediction: A Machine Learning Approach
Creator
Akshithaa Parvathavardhini, K.P.; Chandra, J.
Description
Rainfall variability plays a critical role in agriculture, water resources, and disaster management in India. This study focuses on the usage of a SARIMAX model to analyze and predict rainfall patterns while accounting for both non-seasonal and seasonal components. The model adequately captures seasonal variations, illustrating the relevance of incorporating seasonal factors into forecasting. However, the non-seasonal components did not considerably improve the models performance. Diagnostic tests demonstrate that the model handles autocorrelation satisfactorily; however, the residuals exhibit irregularities, as evidenced by skewness and large tails. While the model has fair prediction accuracy, the findings show areas for development, particularly in fine-tuning non-seasonal dynamics and eliminating residual abnormalities. This research emphasizes the importance of seasonality in rainfall forecasting and lays the framework for future model improvements. The study provides valuable information on rainfall patterns, supporting better planning and management. 2025 IEEE.
Source
2025 IEEE 14th International Conference on Communication Systems and Network Technologies, CSNT 2025;pp.42-46
Date
01-01-2025
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
ARIMA; Climate patterns; Rainfall variability; SARIMAX; Seasonal decomposition; Time series analysis
Coverage
Akshithaa Parvathavardhini K.P., Department of Computer Science Christ (Deemed to be University), Bangalore, India; Chandra J., Department of Computer Science Christ (Deemed to be University), Bangalore, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833153193-5;
Format
online
Language
English
Type
Conference paper

Citation

Akshithaa Parvathavardhini, K.P.; Chandra, J., “AI-Driven Time Series Models for Rainfall Prediction: A Machine Learning Approach,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/25813.

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