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Time Series Analysis of Climatic Change

Time Series Analysis of Climatic Change

Paperback

Probability & Statistics

ISBN10: 6207996127
ISBN13: 9786207996124
Publisher: LAP Lambert Academic Publishing
Published: Jul 24 2025
Pages: 88
Weight: 0.28
Height: 0.21 Width: 6.00 Depth: 9.00
Language: English
This book explores the importance of accurate rainfall forecasting for water resource management, agriculture, and disaster preparedness. It presents a comparative analysis of two forecasting models-Support Vector Regression (SVR) and Seasonal Auto Regressive Integrated Moving Average (SARIMA)-using historical rainfall data from 2008 to 2021 to predict trends from 2022 to 2026. Through statistical and visualization techniques such as trend analysis, moving averages, box plots, heatmaps, Z-scores, and density plots, the study identifies patterns and anomalies in rainfall data. While both models show good predictive ability, SVR demonstrates superior performance, especially in capturing complex, non-linear patterns. The book highlights the advantages of integrating machine learning methods with traditional statistical tools to improve rainfall forecasting and support data-driven decisions in agriculture, environmental planning, and climate resilience.

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Probability & Statistics