报告题目：Fuzzy Modeling and Machine Learning
Fuzzy set theory was first proposed by Prof. Zadeh in 1965. Extension theory is initiated by Prof. Cai in 1983. Fuzzy systems and extenics have been widely used for various applications such as data analysis, product classification, management, fault diagnosis, system optimization, and production prediction. Neural network is a promising new generation of information processing systems that demonstrates the ability to learn, recall, and generalize from training patterns or data. Numerous machine learning approaches are used for feature selection, but they are limited or are not suitable for training unsupervised complex functions with multiple hidden layers. However, a deep learning method can provide predictions on complex functions by using a sequence of nonlinear processing stages to improve the accuracy of nonlinearity measurements. Deep learning, a multilevel deep architecture based on the learning of unsupervised feature extraction algorithms, has already transformed fields such as image processing, speech recognition, and examination of multimodal textual information. This talk will address from the fuzzy modeling, machine learning, extenics, big data mining and system engineering perspective for systems developed to resolve applications involving surface scratch detection, exercise monitoring and control using Kinect and Tensorflow, rehabilitation monitoring and tracking on PD using sensor devices.
报告人简介：Yo-Ping Huang received the Ph.D. degree in electrical engineering from Texas Tech University, Lubbock, TX, USA. He is currently a Professor in the Department of Electrical Engineering, Taipei University of Technology, Taipei, Taiwan, where he served as the Secretary General. He was a Professor and the Dean of Research and Development, the Dean of the College of Electrical Engineering and Computer Science, and the Department Chair with Tatung University, Taipei. His current research interests include fuzzy systems design and modeling, deep learning modeling, intelligent control, medical data mining, and rehabilitation systems design.
Prof. Huang serves as the President of the Taiwan Association of Systems Science and Engineering, Chair of the IEEE SMCS Technical Committee on Intelligent Transportation Systems, and the Chair of the Taiwan SIGSPATIAL ACM Chapter. He was the Chair of IEEE SMCS Taipei Chapter, the Chair of the IEEE CIS Taipei Chapter, and the CEO of the Joint Commission of Technological and Vocational College Admission Committee, Taiwan. Under his leadership, SMC Taipei Chapter was awarded the Outstanding Chapter Awards from both IEEE SMC Society and IEEE Taipei Section in 2016. He is an IET Fellow and an International Association of Grey System and Uncertain Analysis Fellow.