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- W2954435206 abstract "Missing value especially in environmental study is a common problem including in rainfallmodelling. 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 ratioinverse distance correlation weighting method (ONRIDCWM) in solving missing rainfalldata. The simulation study is used to identify the best parameters for correlation powerof p, percentage of missing value and sample size, n of the ONRIDCWM by simulatingfor 10,000 times by varying the value of the parameters systematically. The results of thesimulation are compared with other available weighting methods. The estimated completerainfall data of the target station are compared and assessed with the observed data fromthe neighbouring station using mean, estimated bias (EB) and estimated root mean squareerror (ERMSE). The results show that ONRIDCWM is better than the other weightingmethods for the correlation power of p at least four. For illustration of the weightingmethod, monthly rainfall data from Pahang has used to demonstrate the efficiency of themethod using three error indices: S-Index, mean absolute error (MAE) and correlation, R." @default.
- W2954435206 created "2019-07-12" @default.
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- W2954435206 date "2018-11-01" @default.
- W2954435206 modified "2023-09-27" @default.
- W2954435206 title "Simulation model of biomass-based cogeneration plant" @default.
- W2954435206 hasPublicationYear "2018" @default.
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