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Improved Mold Level Control for Continuous Steel Casting by Fuzzy Logic Control
Kueon, Yeongseob,Xiao, Wendong Institute of Control 1999 Transaction on control, automation and systems eng Vol.1 No.1
This paper gives a simulation study of a new fuzzy logic control(FLC) approach for the mold level control in continuous casting processes. The proposed FLC is PID type hybridizing the conventional fuzzy PI control and Fuzzy PD control with a simplified design scheme. It is shown that, compared with the conventional control, this new control strategy can achieve superior performance for steady-state response and is more robust against process parameter variations and disturbances.
Xiaopeng Niu,Zhiliang Wang,Wendong Xiao,Zhigeng Pan 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.11
Human activity recognition is a main research area of context-aware computing, and is widely used in many applications, such as smart home and elderly care. Smart phone-based human activity recognition is very popular by making use of the embedded inertial sensors. However, there exists the problems of misclassification activities, and how to effectively apply the model trained by known users to new users. To solve these two problems, in this paper, we proposed a novel approach, Uncertainty Sampling based posterior Probability Extreme Learning Machine (USP-ELM), by introducing two strategies: first, we transfer the actual outputs of ELM to posterior probabilities for each instances, and then use uncertainty sampling strategy for confidence level assignment to adapt the training model and improve the classification accuracy. Experimental results show that the proposed approach is more efficient, compared with the existing ELMs.