%0 Journal Article
%A WANG Dezheng1
%A ZHANG Yinong1
%A YANG Fan2
%T Implementation of parallel PLS algorithm of process monitoring using MapReduce
%D 2018
%R 10.3778/j.issn.1002-8331.1709-0005
%J Computer Engineering and Applications
%P 61-65
%V 54
%N 24
%X Partial Least Squares（PLS） has been widely used in multivariate statistical process monitoring methods for industrial processes, and it is computation-intensive and time-demanding when dealing with massive data. To solve this problem to consider time complexity, a novel implementation of parallel partial least squares is proposed using MapReduce, which consists of the parallelization of cross validation. Using Tennessee-Eastman Process data as an example, experiments are conducted on a Hadoop cluster, which is a collection of ordinary computers. The experimental results demonstrate that parallel partial least squares algorithm can handle massive process data, can significantly cut down the modeling time, and gains a basically linear speedup with the number of computers increased, and can be easily scaled up.
%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1709-0005