{ "item_title" : "Time Series Analysis of Climatic Change", "item_author" : [" Mani N", "Rithika S", "Sivakumaran P. K. "], "item_description" : "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.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/6/20/799/612/6207996127_b.jpg", "price_data" : { "retail_price" : "51.00", "online_price" : "51.00", "our_price" : "51.00", "club_price" : "51.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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