Determining the steady-state probability for the daily maximum temperature in Peninsular Malaysia using Markov Chain / Suriani Hassan
The objective of this study was to determine the steady-state probability for the daily maximum temperature in Peninsular Malaysia. Data of daily maximum temperature from Malaysian Meteorological Department were analyzed. Ten stations in Peninsular Malaysia were examined. The transition count, chi-s...
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| Format: | Article |
| Language: | English |
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Universiti Teknologi MARA Cawangan Pulau Pinang
2017
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| Online Access: | https://ir.uitm.edu.my/id/eprint/28807/1/AJ_SURIANI%20HASSAN%20EAJ%2017.pdf |
| _version_ | 1825736912823910400 |
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| author | Hassan, Suriani Hasan, Husna |
| author_facet | Hassan, Suriani Hasan, Husna |
| author_sort | Hassan, Suriani |
| collection | UITM |
| description | The objective of this study was to determine the steady-state probability for the daily maximum temperature in Peninsular Malaysia. Data of daily maximum temperature from Malaysian Meteorological Department were analyzed. Ten stations in Peninsular Malaysia were examined. The transition count, chi-square test, transition probability and steady-state probability were obtained. The steady-state probability results showed that after a sufficiently long time, there was a high probability for the stations to encounter the slightly warm temperature, with the range of maximum temperature from 30.1°C to 34.0°C, except Chuping and Alor Setar tend to be warmer with the range of maximum temperature from 38.1°C to 42.0°C and Muadzam Shah tend to be in warm state with the range of maximum temperature from 34.1°C to 38.0°C. The importance of knowing the steady-state probability of slightly cool, neutral, slightly warm, warm and hot temperature would help the citizens with the awareness and effects of climate warming. |
| first_indexed | 2024-03-06T02:10:05Z |
| format | Article |
| id | uitm.eprints-8807 |
| institution | Universiti Teknologi MARA |
| language | English |
| last_indexed | 2024-03-06T02:10:05Z |
| publishDate | 2017 |
| publisher | Universiti Teknologi MARA Cawangan Pulau Pinang |
| record_format | dspace |
| spelling | uitm.eprints-88072020-03-26T04:42:16Z https://ir.uitm.edu.my/id/eprint/28807/ Determining the steady-state probability for the daily maximum temperature in Peninsular Malaysia using Markov Chain / Suriani Hassan esteem Hassan, Suriani Hasan, Husna Multivariate analysis. Cluster analysis. Longitudinal method Regression analysis. Correlation analysis. Spatial analysis (Statistics) The objective of this study was to determine the steady-state probability for the daily maximum temperature in Peninsular Malaysia. Data of daily maximum temperature from Malaysian Meteorological Department were analyzed. Ten stations in Peninsular Malaysia were examined. The transition count, chi-square test, transition probability and steady-state probability were obtained. The steady-state probability results showed that after a sufficiently long time, there was a high probability for the stations to encounter the slightly warm temperature, with the range of maximum temperature from 30.1°C to 34.0°C, except Chuping and Alor Setar tend to be warmer with the range of maximum temperature from 38.1°C to 42.0°C and Muadzam Shah tend to be in warm state with the range of maximum temperature from 34.1°C to 38.0°C. The importance of knowing the steady-state probability of slightly cool, neutral, slightly warm, warm and hot temperature would help the citizens with the awareness and effects of climate warming. Universiti Teknologi MARA Cawangan Pulau Pinang 2017-08 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/28807/1/AJ_SURIANI%20HASSAN%20EAJ%2017.pdf Determining the steady-state probability for the daily maximum temperature in Peninsular Malaysia using Markov Chain / Suriani Hassan. (2017) ESTEEM Academic Journal <https://ir.uitm.edu.my/view/publication/ESTEEM_Academic_Journal/>, 13. pp. 129-138. ISSN 1675-7939 https://uppp.uitm.edu.my |
| spellingShingle | Multivariate analysis. Cluster analysis. Longitudinal method Regression analysis. Correlation analysis. Spatial analysis (Statistics) Hassan, Suriani Hasan, Husna Determining the steady-state probability for the daily maximum temperature in Peninsular Malaysia using Markov Chain / Suriani Hassan |
| title | Determining the steady-state probability for the daily maximum temperature in Peninsular Malaysia using Markov Chain / Suriani Hassan |
| title_full | Determining the steady-state probability for the daily maximum temperature in Peninsular Malaysia using Markov Chain / Suriani Hassan |
| title_fullStr | Determining the steady-state probability for the daily maximum temperature in Peninsular Malaysia using Markov Chain / Suriani Hassan |
| title_full_unstemmed | Determining the steady-state probability for the daily maximum temperature in Peninsular Malaysia using Markov Chain / Suriani Hassan |
| title_short | Determining the steady-state probability for the daily maximum temperature in Peninsular Malaysia using Markov Chain / Suriani Hassan |
| title_sort | determining the steady state probability for the daily maximum temperature in peninsular malaysia using markov chain suriani hassan |
| topic | Multivariate analysis. Cluster analysis. Longitudinal method Regression analysis. Correlation analysis. Spatial analysis (Statistics) |
| url | https://ir.uitm.edu.my/id/eprint/28807/1/AJ_SURIANI%20HASSAN%20EAJ%2017.pdf |
| work_keys_str_mv | AT hassansuriani determiningthesteadystateprobabilityforthedailymaximumtemperatureinpeninsularmalaysiausingmarkovchainsurianihassan AT hasanhusna determiningthesteadystateprobabilityforthedailymaximumtemperatureinpeninsularmalaysiausingmarkovchainsurianihassan |