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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Main Authors: Saaban, Azizan, Zainudin, Lutfi, Abu Bakar, Mohd Nazari
Format: Conference or Workshop Item
Published: 2015
Subjects:
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author Saaban, Azizan
Zainudin, Lutfi
Abu Bakar, Mohd Nazari
author_facet Saaban, Azizan
Zainudin, Lutfi
Abu Bakar, Mohd Nazari
author_sort Saaban, Azizan
collection UUM
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.
first_indexed 2024-07-04T06:08:31Z
format Conference or Workshop Item
id uum-18746
institution Universiti Utara Malaysia
last_indexed 2024-07-04T06:08:31Z
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spelling uum-187462016-10-04T06:40:47Z https://repo.uum.edu.my/id/eprint/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 doi:10.1063/1.4915657
spellingShingle QA Mathematics
Saaban, Azizan
Zainudin, Lutfi
Abu Bakar, Mohd Nazari
Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis
title 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_short 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
topic QA Mathematics
work_keys_str_mv AT saabanazizan evaluationoflinearinterpolationmethodformissingvalueonsolarradiationdatasetinperlis
AT zainudinlutfi evaluationoflinearinterpolationmethodformissingvalueonsolarradiationdatasetinperlis
AT abubakarmohdnazari evaluationoflinearinterpolationmethodformissingvalueonsolarradiationdatasetinperlis