http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Xin Zhao,Chao Ge,Fangfang Ji,Yajuan Liu 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.11
In the paper, the chaos least squares support vector machine algorithm (Chaos-LS-SVM) is applied. To conduct uncertainty analysis of wind power forecasting, two forecasting algorithms of the probabilistic uncertainty analysis based on the Monte Carlo method and the quantile regression analysis based on Chaos-LS-SVM are discussed. The effectiveness and superiority of the two uncertainty analysis methods in the confidence level of 95%, 90%, and 85% are discussed by simulation analysis, and the confidence interval is given in the corresponding confidence level. The prediction interval coverage probability (PICP) and the prediction interval normalized average width (PINAW) of the two uncertainty methods are compared. In the time scale of 1h-ahead, 4h-ahead, and 6h-ahead, the probabilistic uncertainty analysis based on the Monte Carlo method is suitable. In the time scale of 24h-ahead, the quantile regression analysis based on Chaos-LS-SVM is superior.
Data mining and visualization of urban air pollution
GE CHAO(갈초),Dongwoo Lee(이동우) 한국정보기술학회 2015 Proceedings of KIIT Conference Vol.2015 No.6
With the prosperity of social economy and the progress of mode industrialization, the environment pollution is becoming worse and worse. The environment problem must attract more attention. In order to effectively reduce the pollution, a scientific assessment to the air quality is needed. The question of the modem urban environment air quality management is how to manage the data resources effectively and mine the rich information which contains in these data, displays the information potential and the value fully, promotes the urban environment air quality management level. The data mining technology is examined for effective plan to solve this question.
Chao Ge,Chenlei Chang,Yajuan Liu,Changchun Hua 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.9
The exponential synchronization for a class of neural networks (NNs) based on dynamic event-triggered mechanism (DETM) is researched in this article. Firstly, an unbounded distributed delay is introduced into the NNs. Next, based on the characteristics of the sawtooth structure, an improved bilateral Lyapunov-Krasovskii functional (LKF) is constructed, which involves more information. By using improved integral inequality, some sufficient conditions are achieved for the exponential stability of the synchronization error system. Due to the influence of external factors or internal components, the controller parameter is uncertain. Then, a non-fragile controller is designed based on the decoupling technique. Moreover, a co-design scheme of controller gain and event-triggered matrix is obtained based on the linear matrix inequality technique. Finally, two examples are used to illustrate the validity and feasibility of the presented method.
Stabilization of chaotic systems under variable sampling and state quantized controller
Ge, Chao,Wang, Hong,Liu, Yajuan,Park, Ju H. North-Holland 2018 Fuzzy sets and systems Vol.344 No.-
<P>This paper investigates the problem of stabilization for chaotic systems based on a T-S fuzzy model under sampled-data control and state quantization. A novel Lyapunov-Krasovskii functional (LKF) is introduced to the sampled-data systems. The benefit of the new approach is that the LKF develops more information about the actual sampling pattern. In addition, some symmetric matrices involved in the LKF are not required to be positive definite. Based on a recently introduced Wirtinger-based integral inequality that has been shown to be less conservative than Jensen's inequality, much less conservative stabilization conditions are obtained to ensure the maximal sampling period. Then, the corresponding sampled-data controllers can be synthesized by solving a set of linear matrix inequalities (LMIs). Finally, an illustrative example is given to show the feasibility and effectiveness of the proposed method. (C) 2017 Elsevier B.V. All rights reserved.</P>
Chao Ge,Chang-chun Hua,Xin-Ping Guan 제어·로봇·시스템학회 2014 International Journal of Control, Automation, and Vol.12 No.4
This paper concerns with the problem of asymptotic stability for neutral systems with time-varying delays. With the introduction of delay-decomposition approach, some new delay-dependent stability criteria are established and formulated in the form of linear matrix inequalities. Both constant time delays and time-varying delays have been taken into account. Numerical examples are given to demonstrate the effectiveness and less conservativeness of the proposed methods.
A Highly Integrated Automatic Fiber Optical Gyroscope Sensing Coil Winding System
Shuang-Chao Ge,Rui-Feng Yang,Chen-Xia Guo 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.2
Fiber optic gyroscope (FOG) is a new type of optical sensor used to measure the rotating angular velocity. As the core component, fiber optic coil (FOC) plays a decisive role in the FOG output precision. The manufacturing level and efficiency of FOC have been main factors restricting the application and development of high precision FOG. Precision mechanical positioning method based on the photoelectric devices was researched, and high-performance fully automatic micro mechanical error compensation technique was developed. On these basis, automatic fiber distribution and winding control technology were realized. Eventually a multifunctional system was developed with fiber splitting module, fiber winding module, and calibration module. This system could accomplish automatic preparation of FOC with quadrupolar symmetric pattern according to the parameters set by user. The principle and working flow of each functional module are discussed in details. Experiments show that the system can achieve automatic speed changing, automatic reversing, constant small tension control and precise fiber arrangement. The new designed system greatly improve FOC production efficiency and is conductive to promotinghigh level FOG development.
Chao Liu,Yousef Zandi,Abouzar Rahimi,Yongli Peng,Genwang Ge,Mohamed Amine Khadimallah,Alibek Issakhov,Subbotina Tatyana Yu 국제구조공학회 2021 Smart Structures and Systems, An International Jou Vol.28 No.2
Shear connectors play a major role in the development of composite steel concrete systems. The behavior of shear connectors is usually calculated by push-out measurements. These experiments are expensive and take a lot of time. Soft Computation (SC) may be applied as an additional solution to remove the need for push-out testing. The objective of the research is to explore the implementation, as sub-branches of the SC approaches, of artificial intelligence (AI) techniques for the prediction of advanced C-shaped shear connectors. To this end, multiple push-out tests on these connectors will be carried out and the requisite data is obtained for the AI models. The Grey Wolf Optimizer algorithm (GWO) is built to define the parameters that influence the shear strength of angle connectors. Two regression metrics as determination coefficient (R2) and root mean square (RMSE) were used to measure the results of model. Furthermore, only four parameters in the predictive models are sufficient to provide an extremely precise prediction. It was found that GWO is a faster method and is able to achieve marginally higher output indices than in experiments.