PREDICTION MODEL OF MISSING DATA: A CASE STUDY OF PM10 ACROSS MALAYSIA REGION

Azman, Azid and Saiful Iskandar, Khalit and Hafizan, Juahir (2018) PREDICTION MODEL OF MISSING DATA: A CASE STUDY OF PM10 ACROSS MALAYSIA REGION. Journal of Fundamental and Applied Sciences, 10 (1S). pp. 182-203. ISSN 1112-9867

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Abstract

PM 10 is one of the major concerns that have high potential for harmful effects on human health. Thus, prediction of PM 10 was performed with the objectives to model suitable PM 10 prediction formula to predict the concentration of PM 10 . Imputation methods of EMB-algorithm and nearest neighbor were applied to treat missing data before analyzed by Fit model, MLR and ANN. R 2 obtained for Fit-model, MLR and ANN using imputation method of EMB-algorithm and nearest neighbor are (0.9975, 0.3858), (0.9623, 0.3857) and (0.9975, 0.4025) respectively. Sensitivity analysis (SA) shows humidity, temperature, CO, UVB and O 3 out of fifteen parameters contribute the most to the present of PM 10 concentration. In conclusion, formula for the best PM 10 prediction can be modeled by using ANN or Fit model together with the imputation method of EMB-algorithm.

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