Title :
A PCA-BPN approach for estimating simulation workload in cloud manufacturing
Author_Institution :
Dept. of Ind. Eng. & Syst. Manage., Feng Chia Univ., Taichung, Taiwan
Abstract :
Cloud manufacturing is a novel manufacturing technology that supports factories distributed around the world with ubiquitous accesses to manufacturing resources. Estimating the simulation workload for simulating a factory online is an important topic to cloud manufacturing. To investigate this, a principal component analysis (PCA)-back propagation network (BPN) approach is proposed in this study. The real data of some simulation tasks have been collected to test the proposed methodology. The experimental results supported the superiority of the proposed methodology over some existing methods in terms of the estimation accuracy.
Keywords :
backpropagation; cloud computing; computer aided manufacturing; principal component analysis; ubiquitous computing; PCA-BPN approach; cloud manufacturing; manufacturing technology; principal component analysis-back propagation network; simulation workload estimation; ubiquitous manufacturing resource access; Backpropagation; Computational modeling; Estimation; Genetic programming; Testing; Training; Virtualization; Cloud manufacturing; back propagation network; estimation; principal component analysis; simulation workload; ubiquitous;
Conference_Titel :
Ubiquitous and Future Networks (ICUFN), 2015 Seventh International Conference on
Conference_Location :
Sapporo
DOI :
10.1109/ICUFN.2015.7182658
