人: 洪灵 教授    李自刚  副教授

报告时间: 202387 (周一)  上午9:30-11:30

报告地点: 交通楼608会议室

组织单位: 国重实验室

报告题目一:Fuzzy Generalized Cell Mapping with Adaptive Interpolation (FGCM with AI) for Bifurcation Analysis of Nonlinear Systems with Fuzzy Uncertainties

报告摘要:

 Fuzzy Generalized Cell Mapping (FGCM) method is developed with the help of the Adaptive Interpolation (AI) in the space of fuzzy parameters. The adaptive interpolation on the set-valued fuzzy parameter is introduced in computing the one-step transition membership matrix to enhance the efficiency of the FGCM. For each of initial points in the state space, a coarse database is constructed at first, and then interpolation nodes are inserted into the database iteratively each time errors are examined with the explicit formula of interpolation error until the maximal errors are just under the error bound. With such an adaptively expanded database on hand, interpolating calculations assure the required accuracy with maximum efficiency gains. The new method is termed as Fuzzy Generalized Cell Mapping with Adaptive Interpolation (FGCM-AI), bifurcation analysis shows that the FGCM with AI has a thirtyfold to fiftyfold efficiency over the traditional FGCM to achieve the same analyzing accuracy.

个人简介:

Prof. Dr. Ling Hong received her B.S. from Gansu University of Technology in 1982 and M.S. and Ph.D. degree from Xi’an Jiaotong University in 1997 and 2001, respectively. She worked as a postdoctoral fellow at the University of Delaware in USA from 2004 to 2006. Dr. Hong is currently a professor in the School of Aerospace at Xi’an Jiaotong University. She was nominated for ‘The Best 100 Ph.D. Theses of China’ in 2004 and was awarded the Nature Science Award by MOE in 2003 and by Shaanxi province in 2021. Her research interests include global analysis, bifurcation and chaos for nonlinear and stochastic and fuzzy uncertain dynamic systems.

报告题目二:Several Advances in Space Discretization method for Global Analysis of Nonlinear Systems

报告摘要:

 Space discretization is an excellent strategy to efficiently approximating and visualizing physical structures or systematic functions, because of its natural features on error-tolerance and noise-tolerance. However, the complete global analysis with an enough fine discretized resolution invariably confronts a daunting computational burden, expecially for high-dimensional and complex systems. The challenge, known as the curse of dimensions, is manifested by exponentially explosive growth in the number of grids and samples required, as the increase of dimensions. To conquer the unaffordable computing cost, we develop several new numerical algorithms based on the idea of space discretization, namely, the parallel subdomain synthesis of cell mapping (PSSCM) for capturing model-based global invariant sets in higher-dimensional dynamical systems, the subspace expanding technique (SET) for global zero finding of MDOF nonlinear systems, and boundary-oriented incremental learning method (BOILM) for predicting data-based basins of attraction in state space and parameter space with high dimensions. We show that the space discretization can build a computation framework capable of achieving a controllable region division or dimension expansion. Several examples of typical nonlinear systems are presented to demonstrate the remarkable performance enhancements, ranging from several-fold to several hundred thousand-fold improvements in computational efficiency, achieved by the proposed algorithms.

个人简介:

李自刚,西安科技大学副教授,机械工程学科项目博导。毕业于西安交通大学获博士学位,美国UC Merced博士后,教育部中西部青年骨干教师天津大学高级访问学者。现任西安科技大学理学院副院长,兼任陕西省振动工程学会学会常务理事、中国振动工程学会转子动力学专业委员会理事。研究兴趣主要包括数据驱动与机器学习智能算法、非线性全局动力学与控制、旋转机械动力学、海洋洋流动力学等领域。近年来,主持国家自然科学基金青年项目、面上项目,陕西省科技厅项目,校优青人才项目等。在《Nonlinear Dynamics》、《International Journal of Bifurcation and Chaos》、《力学学报》等国内外著名期刊和会议发表学术论文30余篇,出版《非线性动力学丛书—完整约束下转子-轴承系统非线性振动》专著1部,授权国家专利3项。担任国家自然科学基金同行评议专家,美国机械工程师协会(ASME)多种国际期刊特邀评审人。分别获陕西省科学技术一等奖、三等奖,陕西高等学校科学技术奖特等奖,西安市科学技术二等奖,陕西省振动工程学会青年科技奖等。

 

科技处   

2023年31日

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