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Plenary Speakers

 

Prof.Yuhui Shi (Professor      of Electronic and Electrical Engineering, Xi'an Jiaotong-Liverpool      University)      

    

    Dr. Yuhui Shi has been a professor in the      Department of Electrical and Electronic Engineering at Xi’an      Jiaotong-Liverpool University (XJTLU), Suzhou, China, since 2008. Dr. Shi      was with Electronic Data Systems Corporation (EDS) in Indiana from 1998      to 2007. He is the editor-in-chief of the International Journal of Swarm      Intelligence Research and was an associate editor of the IEEE      Transactions on Evolutionary Computation from January, 2003, to December,      2013. Dr. Shi co-authored a book on swarm intelligence with Dr. James      Kennedy and Dr. Russell C. Eberhart, and another book, Computational      Intelligence: Concept to Implementation, with Dr. Russell C. Eberhart.      

 

Title      Developmental      Brain Storm Optimization Algorithms

 

Abstract     

          Among all population-based evolutionary computation and/or swarm      intelligence algorithms, even though most of them are nature-inspired      and/or bio-inspired, especially are inspired by objects with low level      intelligence, they have shown great capability to solve complex and      difficult optimization problems. Human being is the most intelligent      animal on the earth, therefore, it is natural to expect that optimization      algorithms motivated and/or inspired from collective behavior of human      being could be superior to the optimization algorithms motivated and/or      inspired by objects with low level intelligence. In this talk, the brain      storm optimization (BSO) algorithms will be introduced, which was      inspired by one of the human being problem solving skills, that is, the      brainstorming process. First, the brainstorming process will be      introduced, followed by the development of the brain storm optimization      algorithm; then, the framework of developmental learning algorithms will      be discussed; finally the BSO algorithm will be looked at from the      developmental learning perspective.



 

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