%0 Journal Article
%@ 21945357
%A El-Harbawi, M.
%A Trang, P.T.K.
%D 2016
%F scholars:8017
%I Springer Verlag
%J Advances in Intelligent Systems and Computing
%K Algorithms; Health hazards; Learning algorithms; Linear regression; MATLAB, American conference of governmental industrial hygienists; Experimental assessment; Group contribution method; Multiple linear regressions; Occupational Exposure Limits; OELs; QSPR; Quantitative structure property relationships, Health
%P 395-402
%R 10.1007/978-3-662-47926-1₃₈
%T Development of mathematical model using group contribution method to predict exposure limit values in air for safeguarding health
%U https://khub.utp.edu.my/scholars/8017/
%V 382
%X Occupational Exposure Limits (OELs) are representing the amount of a workplace health hazard that most workers can be exposed to without harming their health. In this work, a new Quantitative Structure Property Relationships (QSPR) model to estimate occupational exposure limits values has been developed. The model was developed based on a set of 100 exposure limit values, which were published by the American Conference of Governmental Industrial Hygienists (ACGIH). MATLAB software was employed to develop the model based on a combination between Multiple Linear Regression (MLR) and polynomial models. The results showed that the model is able to predict the exposure limits with high accuracy, R2 = 0.9998. The model can be considered scientifically useful and convenient alternative to experimental assessments. © Springer-Verlag Berlin Heidelberg 2016.
%Z cited By 1; Conference of 2nd International Conference on Harmony Search Algorithm, ICHSA 2015 ; Conference Date: 19 August 2015 Through 21 August 2015; Conference Code:129199