کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
432592 688966 2006 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Parallel EDAs to create multivariate calibration models for quantitative chemical applications
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Parallel EDAs to create multivariate calibration models for quantitative chemical applications
چکیده انگلیسی

This paper describes the application of a collection of data mining methods to solve a calibration problem in a quantitative chemistry environment. Experimental data obtained from reactions which involve known concentrations of two or more components are used to calibrate a model that, later, will be used to predict the (unknown) concentrations of those components in a new reaction. This problem can be seen as a selection+prediction one, where the goal is to obtain good values for the variables to predict while minimizing the number of the input variables needed, taking a small subset of really significant ones. Initial approaches to the problem were principal components analysis and filtering combined with two prediction techniques: artificial neural networks and partial least squares regression. Finally, a parallel estimation of distribution algorithm was used to reduce the number of variables to be used for prediction, yielding the best models for all the considered problems.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Parallel and Distributed Computing - Volume 66, Issue 8, August 2006, Pages 1002-1013