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Journal of Artificial Intelligence, Machine Learning, and Computing

Peer-Reviewed Academic Journal
Research Article

EXPLORING DAILY TEMPERATURE VARIABILITY IN BANGKOK: A TIME SERIES ANALYSIS

Authors & Affiliations
Pimchanok Kanyawee Srisuk
Demonstration School of Nakhon Ratchasima Rajabhat University, Thailand
Warisara Anong Phromphong
Demonstration School of Nakhon Ratchasima Rajabhat University, Thailand
Kritsada Chonlasin
Department of Computational Science and Digital Technology, Thammasat University, Thailand
Published: December 3, 2024
Volume 12, Issue 4 (2024)
Article ID: 621
Peer-Reviewed
Open Access
Abstract

In the face of rapidly changing global climate patterns attributed to various human activities and the increasing concentrations of greenhouse gases, accurate temperature forecasting has become a vital aspect of climate research. This study focuses on Bangkok, the bustling capital and economic hub of Thailand, due to its significance in the nation's economic and cultural landscape. The research aims to develop reliable statistical models for predicting daily maximum and minimum temperatures in Bangkok, facilitating better preparation and response to meteorological phenomena. Temperature variations in this region are influenced by a multitude of factors, including sun exposure, ground conditions, ocean currents, geographical location, and cloud cover. By utilizing simple time series analysis, this study strives to provide valuable insights for urban planning and disaster prevention, ultimately helping residents mitigate potential losses or challenges stemming from changing climate conditions.

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