[预告]04.16讲座《大数据系统智能模型的建立及深入之例证》


  题目:大数据系统智能模型的建立及深入之例证
     Intelligent Modelling of Big Data Systems with In-Depth Illustrations

  时间:2016年4月16日周六,上午10:00

  地点:英东教育楼A区217会议室

  主持人:郭平 教授

  主讲人:王启旭(Chi-Hsu Wang)教授

  主讲人简介:

  王启旭教授,IEEE Fellow。He received the B.S. degree in control engineering from the National Chiao Tung University, Hsinchu, Taiwan, the M.S. degree in computer science from the National Tsing Hua University, Hsinchu, and the Ph.D. degree in electrical and computer engineering from the University of Wisconsin, Madison, WI, USA, in 1976, 1978, and 1986, respectively. He was an Associate Professor in 1986 and a Professor in 1990 with the Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. He is currently a Professor with the Department of Electrical Engineering, National Chiao Tung University. He has been the Adjunct Professor with North East University, Qinhuangdao, China, since 2014. His current research interests and publications include in the areas of digital control, fuzzy-neural-network, intelligent control, adaptive control, and robotics.

  讲座简介:

  
The Big Data Systems (BDSs) have been so popular since 2000. The purpose of this talk is not to illustrate BDSs, but to explore its kernel issue, i.e., the modelling of BDS. In the implementation of BDSs, the conventional mathematical techniques for data analysis have sometimes failed to perform the modelling of BDSs. It may due to the enormous amount of data, or the data structure behind the BDSs is beyond the imagination of classical people. To overcome this potential barrier, this talk will explore the modelling of BDSs by intelligent techniques. A very important finding about the capacity of Fuzzy Neural Networks (FNNs) will be explained first. This capacity issue with intelligent modelling has been actually applied to a real application of water monitoring system by remote sensing approach. This successful benchmark using intelligent modelling with capacity constraint for BDSs is a very positive sign in this research area. Further potential enhancements and the relation with deep training will also be discussed.

 



 


 

(系统科学学院)