管科学术论坛（2018年第14期）

报告时间：2018年10月22日（星期一）上午9:30- 11:00

报告地点：燕山校区逸夫楼621

报告题目：Decomposed Fuzzy Systems

报告人：台湾科技大学苏顺丰教授

Abstract:

In the talk, a novel fuzzy structure termed as the decomposed fuzzy system (DFS) is proposed to act as the fuzzy approximator. The proposed structure is to decompose each fuzzy variable into layers of fuzzy systems and each layer is to characterize one traditional fuzzy set. Similar to forming fuzzy rules in traditional fuzzy systems, layers from different variables will form the so-called component fuzzy systems. The structure of DFS is proposed to facilitate minimum distribution learning effects among component fuzzy systems so that the learning can be very efficient. It can be seen from our experiments that even when the rule number increases, the learning time in terms of cycles is still almost constant. It can also be found that the function approximation capability and learning efficiency of the DFS are much better than that of the traditional fuzzy systems when employed in adaptive fuzzy control systems. Besides, in order to further reduce the computational burden, a simplified DFS is proposed in this study to satisfy possible real time constraints required in many applications. From our simulation results, it can be seen that the simplified DFS can perform fairly with a more concise decomposition structure. Furthermore, when used in modeling, the proposed DFS not only can have much faster convergent speed, but also can achieve a smaller testing error than those of other fuzzy systems.

报告人简介:

苏顺丰教授，1991年获美国普渡大学博士学位，现为台湾科技大学电子工程系讲席教授，IEEE Fellow及CACS Fellow，国际模糊系统协会（IFSA）前任主席，IEEE系统、人和控制论协会（SMC）的理事会成员和青年分会主席。苏教授担任过多个国际会议的大会总主席或程序委员会主席，在机器人、智能控制、模糊系统、神经网络等领域发表论文300余篇。苏教授目前的研究领域包括计算智能、机器学习、虚拟现实仿真、智能交通系统、智能家居、机器人、智能控制等。苏教授现为著名国际期刊IEEE Transactions on Fuzzy Systems、IEEE Transactions on Cybernetics、IEEE Access的副主编，Journal of the Chinese Institute of Engineers期刊的领域编委，SCI二区期刊International Journal of Fuzzy Systems的主编。