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RISS 인기검색어
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- 저자 : Shiyou Chen (검색결과 4 건)
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Huilin Liu,YuCheng Ma,Xushan Chen,Meng Zhou,Shiyou Chen 한국통신학회 2020 한국통신학회 APNOMS Vol.2020 No.09
The reliability of the power communication network is important to the stable operation of the power grid. Existing studies on the reliability evaluation of power communication networks rarely consider the factors of environmental changes. In fact, changes in the working environment of power service routing will affect the normal operation of the network. This paper studies the reliability evaluation method of power communication network based on environmental factors. The normal cloud model method is used to model the multiple environmental factors in the power communication network, and a controlled hybrid stochastic petri network is used to model and analyze the power transmission system with backup route. In simulation experiments, we compare our algorithm with the contrast algorithm that not considering the impact of environmental factors. The results show that our algorithm can well reflect the impact of changes in environmental factors on the reliability of the system, and more in line with the actual reliability changes of the power service transmission system.
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Design and simulation of self-organizing network routing algorithm based on Q-learning
Yuejia Dou,Huilin Liu,Liangkang Wei,Shiyou Chen 한국통신학회 2020 한국통신학회 APNOMS Vol.2020 No.09
With the continuous advancement of computer network communication technology, traditional wired and wireless networks are limited by cables and base stations, and are not applicable in some application scenarios. Therefore, mobile wireless communication methods have attracted more and more attention. Due to its dynamic topology and self-organizing without center, the self-organizing network can form a mobile temporary multi-hop mobile communication network through multiple wireless communication devices, which can well meet the above requirements. At present, research on self-organizing networks mainly focuses on routing protocols. The main types are based on network topology information and location information. This paper designs a routing algorithm based on link reliability. The algorithm fully considers the self-organizing network link information, and models the node"s sending and receiving work as a Markov decision process, and uses Q-learning to demodulate. This article used NS2 for network simulation and analysis and comparison of performance indicators with traditional routing algorithms.
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Self-Regulation Mechanism for Charged Point Defects in Hybrid Halide Perovskites
Walsh, Aron,Scanlon, David O,Chen, Shiyou,Gong, X G,Wei, Su-Huai WILEY-VCH Verlag 2015 Angewandte Chemie Vol.54 No.6
<P>Hybrid halide perovskites such as methylammonium lead iodide (CH<SUB>3</SUB>NH<SUB>3</SUB>PbI<SUB>3</SUB>) exhibit unusually low free-carrier concentrations despite being processed at low-temperatures from solution. We demonstrate, through quantum mechanical calculations, that an origin of this phenomenon is a prevalence of ionic over electronic disorder in stoichiometric materials. Schottky defect formation provides a mechanism to self-regulate the concentration of charge carriers through ionic compensation of charged point defects. The equilibrium charged vacancy concentration is predicted to exceed 0.4 % at room temperature. This behavior, which goes against established defect conventions for inorganic semiconductors, has implications for photovoltaic performance.</P>
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Collaborative optimization of cutterhead for mass, mode frequency and fatigue life
Jun Ma,Chunyang Yin,Zhonghua Zhou,Shiyou Chen 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.7
To reduce energy consumption and improve service stability and security, various design methods of cutterhead based on lightweight, modal optimization and life prediction were adopted. In the present work, a multi-disciplinary design optimization (MDO) methodology is presented and subsequently applied to the development of cutterhead. According to the requirements of the cutterhead process and the results of sensitivity analysis, the design parameters of each discipline were determined. To alleviate the computational cost caused by calling the results of finite element method (FEM) in design optimization, the Kriging model was employed to approximate the highly nonlinear implicit relationship between the mode frequency, fatigue life and the design parameters. Then, the system-level optimization model and the subsystem-level optimization model of mass, mode frequency and fatigue life were established based on collaborative optimization (CO). Finally, genetic algorithm (GA) was used for iterative optimization between the system-level and subsystem-level model to obtain the overall optimization results. The results showed that the mass of the cutterhead was finally reduced from 90.4 t to 88.5 t, the first-order modal frequency raised from 32 HZ to 37 HZ, and the fatigue life raised from 3.0E5 cycles to 5.5E5 cycles.
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