技能报告:Optimal way to optimize using optimized randomness and its connection to fractional calculus

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报告人:YangQuan Chen (陈阳泉) 导员,博导(加州企业,默塞德分企业)

时间:2019年7月30日下午16:00-17:00                

地点:数学部713室

联部人:袁利国 


报告摘要:In this talk, first I will show 1) in swarm based search (such as PSO – particle swarm optimization)  using randomness with different heavy-tailed distributions, the search performance can be further optimized beyond Levy; 2)  the connection of heavytailedness and fractional calculus. It is hoped that this talk will open new investigations in new optimal ways to optimize using optimized randomness with the help of fractional calculus in this bigdata and machine learning era. 


报告人概况:陈阳泉导员,特点生导员,现任职于美国加州企业默塞德分企业工程企业,主要研讨领域为分数阶微积分理论及应用,分布式测量及基于移动实行器传感器网络的分布式参数部统的分布式控制,复杂信号的分数阶信号处理理论及应用,智慧机电一体化与控制,小型无人机多谱遥感及精准农业应用等。陈导员是全球刊物IFAC Mechatronics, Nonlinear Dynamics, FCAA (Fractional Calculus and Applied Analysis); Springer Journal of Intelligent & Robotic Systems; 和 Springer Intelligent Service Robotics的副主编. International Journal of Advanced Robotic Systems (IJARS) 的田野机器人领域主编. 陈导员曾是全球刊物IFAC Control Engineering Practice; IEEE Transactions on Control Systems Technology; IET Control Theory and Applications; ISA Transactions,ASME J. of Dynamic Systems, Measurement and Control的副主编。发表作文数百篇,美国专利十几个,研讨专著和教科书近20部,其中ESI 高备引作文10余篇,SCI收录250余篇,Publon引用12500余次 (H-index 56), 谷歌技能搜索引用超过三万次(H-index 79). 他是2018全球高被引学者之一(Clarivate Analytics Inc.).


欢迎广大同事参加!


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