Monte Carlo simulation convergences' percentage and position in future reliability evaluation
Reliability assessment is a needed assessment in today's world. It is required not only for system design but also to ensure the power delivered reaches the consumer. It is usual for fault to occur, but it is best if the fault can be predicted and the way to overcome it ca...
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| Format: | Article |
| Language: | English |
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Institute of Advanced Engineering and Science (IAES)
2022
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| Online Access: | https://umpir.ump.edu.my/id/eprint/44919/ http://doi.org/10.11591/ijece.v12i6.pp6218-6227 |
| _version_ | 1848827336471871488 |
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| author | Nur Nabihah Rusyda, Roslan Noor Fatin Farhanie, Mohd Fauzi Mohd Ikhwan, Muhammad Ridzuan |
| author_facet | Nur Nabihah Rusyda, Roslan Noor Fatin Farhanie, Mohd Fauzi Mohd Ikhwan, Muhammad Ridzuan |
| author_sort | Nur Nabihah Rusyda, Roslan |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Reliability assessment is a needed assessment in today's world. It is required not only for system design but also to ensure the power delivered reaches the consumer. It is usual for fault to occur, but it is best if the fault can be predicted and the way to overcome it can be prepared in advance. Monte Carlo simulation is a standard method of assessing reliability since it is a time-based evaluation that nearly represents the actual situation. However, sequential Monte Carlo (SMC) typically took long-time simulation. A convergence element can be implemented into the simulation to ensure that the time taken to compute the simulation can be reduced. The SMC can be done with and without convergence. SMC with convergence has high accuracy compared to the SMC without convergence, as it takes a long time and has a high possibility of not getting accurate output. In this research, the SMC is subjected to five different convergence items to determine which converge simulation is the fastest while providing better performance for reliability evaluation. There are two types of convergence positions, namely input convergence and output convergence. Overall, output convergence shows the best result compared to input convergence. |
| first_indexed | 2025-11-15T03:59:06Z |
| format | Article |
| id | ump-44919 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:59:06Z |
| publishDate | 2022 |
| publisher | Institute of Advanced Engineering and Science (IAES) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-449192025-08-05T03:41:38Z https://umpir.ump.edu.my/id/eprint/44919/ Monte Carlo simulation convergences' percentage and position in future reliability evaluation Nur Nabihah Rusyda, Roslan Noor Fatin Farhanie, Mohd Fauzi Mohd Ikhwan, Muhammad Ridzuan QA Mathematics TA Engineering (General). Civil engineering (General) Reliability assessment is a needed assessment in today's world. It is required not only for system design but also to ensure the power delivered reaches the consumer. It is usual for fault to occur, but it is best if the fault can be predicted and the way to overcome it can be prepared in advance. Monte Carlo simulation is a standard method of assessing reliability since it is a time-based evaluation that nearly represents the actual situation. However, sequential Monte Carlo (SMC) typically took long-time simulation. A convergence element can be implemented into the simulation to ensure that the time taken to compute the simulation can be reduced. The SMC can be done with and without convergence. SMC with convergence has high accuracy compared to the SMC without convergence, as it takes a long time and has a high possibility of not getting accurate output. In this research, the SMC is subjected to five different convergence items to determine which converge simulation is the fastest while providing better performance for reliability evaluation. There are two types of convergence positions, namely input convergence and output convergence. Overall, output convergence shows the best result compared to input convergence. Institute of Advanced Engineering and Science (IAES) 2022 Article PeerReviewed pdf en cc_by_sa_4 https://umpir.ump.edu.my/id/eprint/44919/1/Monte%20Carlo%20simulation%20convergences%27%20percentage%20and%20position%20in%20future.pdf Nur Nabihah Rusyda, Roslan and Noor Fatin Farhanie, Mohd Fauzi and Mohd Ikhwan, Muhammad Ridzuan (2022) Monte Carlo simulation convergences' percentage and position in future reliability evaluation. International Journal of Electrical and Computer Engineering (IJECE), 12 (6). pp. 6218-6227. ISSN 2088-8708. (Published) http://doi.org/10.11591/ijece.v12i6.pp6218-6227 http://doi.org/10.11591/ijece.v12i6.pp6218-6227 http://doi.org/10.11591/ijece.v12i6.pp6218-6227 |
| spellingShingle | QA Mathematics TA Engineering (General). Civil engineering (General) Nur Nabihah Rusyda, Roslan Noor Fatin Farhanie, Mohd Fauzi Mohd Ikhwan, Muhammad Ridzuan Monte Carlo simulation convergences' percentage and position in future reliability evaluation |
| title | Monte Carlo simulation convergences' percentage and position in future reliability evaluation |
| title_full | Monte Carlo simulation convergences' percentage and position in future reliability evaluation |
| title_fullStr | Monte Carlo simulation convergences' percentage and position in future reliability evaluation |
| title_full_unstemmed | Monte Carlo simulation convergences' percentage and position in future reliability evaluation |
| title_short | Monte Carlo simulation convergences' percentage and position in future reliability evaluation |
| title_sort | monte carlo simulation convergences' percentage and position in future reliability evaluation |
| topic | QA Mathematics TA Engineering (General). Civil engineering (General) |
| url | https://umpir.ump.edu.my/id/eprint/44919/ https://umpir.ump.edu.my/id/eprint/44919/ https://umpir.ump.edu.my/id/eprint/44919/ http://doi.org/10.11591/ijece.v12i6.pp6218-6227 |