skip to main content

SciTech ConnectSciTech Connect

Title: Application of Markov chain model to daily maximum temperature for thermal comfort in Malaysia

The Markov chain’s first order principle has been widely used to model various meteorological fields, for prediction purposes. In this study, a 14-year (2000-2013) data of daily maximum temperatures in Bayan Lepas were used. Earlier studies showed that the outdoor thermal comfort range based on physiologically equivalent temperature (PET) index in Malaysia is less than 34°C, thus the data obtained were classified into two state: normal state (within thermal comfort range) and hot state (above thermal comfort range). The long-run results show the probability of daily temperature exceed TCR will be only 2.2%. On the other hand, the probability daily temperature within TCR will be 97.8%.
Authors:
;  [1]
  1. Pusat Pengajian Sains Matematik Universiti Sains Malaysia, 11800 Pulau Pinang (Malaysia)
Publication Date:
OSTI Identifier:
22492506
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 1682; Journal Issue: 1; Conference: SKSM22: 22. National symposium on mathematical sciences - Strengthening research and collaboration of mathematical sciences in Malaysia, Selangor (Malaysia), 24-26 Nov 2014; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; AMBIENT TEMPERATURE; CLIMATE MODELS; FORECASTING; MALAYSIA; MARKOV PROCESS; METEOROLOGY; PROBABILITY; THERMAL COMFORT