TY  - JOUR
Y1  - 2016///
VL  - 382
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946762044&doi=10.1007%2f978-3-662-47926-1_38&partnerID=40&md5=630714ffe3e7c72a3e21dbc8de3a3895
JF  - Advances in Intelligent Systems and Computing
A1  - El-Harbawi, M.
A1  - Trang, P.T.K.
KW  - Algorithms; Health hazards; Learning algorithms; Linear regression; MATLAB
KW  -  American conference of governmental industrial hygienists; Experimental assessment; Group contribution method; Multiple linear regressions; Occupational Exposure Limits; OELs; QSPR; Quantitative structure property relationships
KW  -  Health
ID  - scholars8017
N2  - 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.
SN  - 21945357
PB  - Springer Verlag
EP  - 402
AV  - none
TI  - Development of mathematical model using group contribution method to predict exposure limit values in air for safeguarding health
SP  - 395
N1  - 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
ER  -