Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis
This paper intends to reveal the ability of the linear interpolation method to predict missing values in solar radiation time series. Reliable dataset is equally tends to complete time series observed dataset.The absence or presence of radiation data alters long-term variation of solar radiation mea...
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my.uum.repo.187462016-10-04T06:40:47Z http://repo.uum.edu.my/18746/ Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis Saaban, Azizan Zainudin, Lutfi Abu Bakar, Mohd Nazari QA Mathematics This paper intends to reveal the ability of the linear interpolation method to predict missing values in solar radiation time series. Reliable dataset is equally tends to complete time series observed dataset.The absence or presence of radiation data alters long-term variation of solar radiation measurement values.Based on that change, the opportunities to provide bias output result for modelling and the validation process is higher.The completeness of the observed variable dataset has significantly important for data analysis.Occurrence the lack of continual and unreliable time series solar radiation data widely spread and become the main problematic issue. However, the limited number of research quantity that has carried out to emphasize and gives full attention to estimate missing values in the solar radiation dataset. 2015 Conference or Workshop Item PeerReviewed Saaban, Azizan and Zainudin, Lutfi and Abu Bakar, Mohd Nazari (2015) Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis. In: International Conference on Mathematics, Engineering and Industrial Applications 2014, 28–30 May 2014, Penang, Malaysia. http://doi.org/10.1063/1.4915657 doi:10.1063/1.4915657 |
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QA Mathematics Saaban, Azizan Zainudin, Lutfi Abu Bakar, Mohd Nazari Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis |
| description |
This paper intends to reveal the ability of the linear interpolation method to predict missing values in solar radiation time series. Reliable dataset is equally tends to complete time series observed dataset.The absence or presence of radiation data alters long-term variation of solar radiation measurement values.Based on that change, the opportunities to provide bias output result for modelling and the validation process is higher.The completeness of the observed variable dataset has significantly important for data analysis.Occurrence the lack of continual and unreliable time series solar radiation data widely spread and become the main problematic issue. However, the limited number of research quantity that has carried out to emphasize and gives full attention to estimate missing values in the solar radiation dataset. |
| format |
Conference or Workshop Item |
| author |
Saaban, Azizan Zainudin, Lutfi Abu Bakar, Mohd Nazari |
| author_facet |
Saaban, Azizan Zainudin, Lutfi Abu Bakar, Mohd Nazari |
| author_sort |
Saaban, Azizan |
| title |
Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis |
| title_short |
Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis |
| title_full |
Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis |
| title_fullStr |
Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis |
| title_full_unstemmed |
Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis |
| title_sort |
evaluation of linear interpolation method for missing value on solar radiation dataset in perlis |
| publishDate |
2015 |
| url |
http://repo.uum.edu.my/18746/ http://doi.org/10.1063/1.4915657 |
| _version_ |
1644282524236513280 |
| score |
13.250246 |