Accelerated Particle Swarm Optimization and Support Vector Machine for Income Prediction and Project Scheduling
Xin-She Yang, Suash Deb, Simon Fong
Journal of Information Technology Review, Vol. 2, No. 3, 2011.
DOI: 
Link: http://www.dline.info/jitr/fulltext/v2n3/2.pdf
Abstract:
Accelerated Particle Swarm Optimization has potential i n many applications and the business sector is one in such wider scope. Coupled with the support vector machine and metaheuristics the particle swarm optimization is now widely used in solving tough optimization problems. By considering the potential features of these two, we have developed an integrated framework for solving business optimization problems. Basically the proposed APSO-SVM to production optimization is used followed by the income prediction and project scheduling. Finally we tested the framework both by parametric studies as well as discussing the advantages of the proposed metaheuristic SVM.