Time Series Analysis of Climatic Change Trends in Temperature and Rainfall. DE
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- Englisch ausgewählt
Fr. 61.90
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
24.07.2025
Verlag
LAP LAMBERT Academic PublishingSeitenzahl
88
Maße (L/B/H)
22/15/0.6 cm
Gewicht
149 g
Sprache
Englisch
ISBN
978-620-7-99612-4
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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