Simulation model of biomass-based cogeneration plant
Missing value especially in environmental study is a common problem including in rainfall modelling. Incomplete data will affect the accuracy and efficiency in any modelling process. In this study, simulation method is used to demonstrate the efficiency of the old normal ratio inverse distance co...
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| Format: | Conference or Workshop Item |
| Language: | English English |
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2018
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| Online Access: | http://umpir.ump.edu.my/id/eprint/24176/1/34.%20Simulation%20study%20of%20adjusted%20spatial%20weighting%20method.pdf http://umpir.ump.edu.my/id/eprint/24176/2/34.1%20Simulation%20study%20of%20adjusted%20spatial%20weighting%20method.pdf |
| _version_ | 1796993228237438976 |
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| author | Muhammad Az-Zuhri, Azman Roslinazairimah, Zakaria Siti Zanariah, Satari |
| author_facet | Muhammad Az-Zuhri, Azman Roslinazairimah, Zakaria Siti Zanariah, Satari |
| author_sort | Muhammad Az-Zuhri, Azman |
| collection | UMP |
| description | Missing value especially in environmental study is a common problem including in rainfall
modelling. Incomplete data will affect the accuracy and efficiency in any modelling process.
In this study, simulation method is used to demonstrate the efficiency of the old normal ratio
inverse distance correlation weighting method (ONRIDCWM) in solving missing rainfall
data. The simulation study is used to identify the best parameters for correlation power
of p, percentage of missing value and sample size, n of the ONRIDCWM by simulating
for 10,000 times by varying the value of the parameters systematically. The results of the
simulation are compared with other available weighting methods. The estimated complete
rainfall data of the target station are compared and assessed with the observed data from
the neighbouring station using mean, estimated bias (EB) and estimated root mean square
error (ERMSE). The results show that ONRIDCWM is better than the other weighting
methods for the correlation power of p at least four. For illustration of the weighting
method, monthly rainfall data from Pahang has used to demonstrate the efficiency of the
method using three error indices: S-Index, mean absolute error (MAE) and correlation, R. |
| first_indexed | 2024-03-06T12:31:02Z |
| format | Conference or Workshop Item |
| id | UMPir24176 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-03-06T12:31:02Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | UMPir241762019-05-21T03:39:53Z http://umpir.ump.edu.my/id/eprint/24176/ Simulation model of biomass-based cogeneration plant Muhammad Az-Zuhri, Azman Roslinazairimah, Zakaria Siti Zanariah, Satari Q Science (General) Missing value especially in environmental study is a common problem including in rainfall modelling. Incomplete data will affect the accuracy and efficiency in any modelling process. In this study, simulation method is used to demonstrate the efficiency of the old normal ratio inverse distance correlation weighting method (ONRIDCWM) in solving missing rainfall data. The simulation study is used to identify the best parameters for correlation power of p, percentage of missing value and sample size, n of the ONRIDCWM by simulating for 10,000 times by varying the value of the parameters systematically. The results of the simulation are compared with other available weighting methods. The estimated complete rainfall data of the target station are compared and assessed with the observed data from the neighbouring station using mean, estimated bias (EB) and estimated root mean square error (ERMSE). The results show that ONRIDCWM is better than the other weighting methods for the correlation power of p at least four. For illustration of the weighting method, monthly rainfall data from Pahang has used to demonstrate the efficiency of the method using three error indices: S-Index, mean absolute error (MAE) and correlation, R. 2018-11 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24176/1/34.%20Simulation%20study%20of%20adjusted%20spatial%20weighting%20method.pdf pdf en http://umpir.ump.edu.my/id/eprint/24176/2/34.1%20Simulation%20study%20of%20adjusted%20spatial%20weighting%20method.pdf Muhammad Az-Zuhri, Azman and Roslinazairimah, Zakaria and Siti Zanariah, Satari (2018) Simulation model of biomass-based cogeneration plant. In: Simposium Kebangsaan Sains Matematik Ke 26 (SKSM26) 2018 , 28 - 29 November 2018 , Universiti Malaysia Sabah, Kota Kinabalu Sabah. pp. 1-8.. (Submitted) http://www.ums.edu.my/fssa/index.php/en/sksm26 |
| spellingShingle | Q Science (General) Muhammad Az-Zuhri, Azman Roslinazairimah, Zakaria Siti Zanariah, Satari Simulation model of biomass-based cogeneration plant |
| title | Simulation model of biomass-based cogeneration plant |
| title_full | Simulation model of biomass-based cogeneration plant |
| title_fullStr | Simulation model of biomass-based cogeneration plant |
| title_full_unstemmed | Simulation model of biomass-based cogeneration plant |
| title_short | Simulation model of biomass-based cogeneration plant |
| title_sort | simulation model of biomass based cogeneration plant |
| topic | Q Science (General) |
| url | http://umpir.ump.edu.my/id/eprint/24176/1/34.%20Simulation%20study%20of%20adjusted%20spatial%20weighting%20method.pdf http://umpir.ump.edu.my/id/eprint/24176/2/34.1%20Simulation%20study%20of%20adjusted%20spatial%20weighting%20method.pdf |
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