期刊：
Physica A-Statistical Mechanics and its Applications,2018年494:140-162 ISSN：0378-4371
通讯作者：
Zhu, Yueying
作者机构：
[Wang, Qiuping A.; Zhu, Yueying] Le Mans Univ, IMMM, UMR CNRS 6283, F-72085 Le Mans, France.;[Zhu, Yueying; Li, Wei; Cai, Xu] Cent China Normal Univ, Complex Sci Ctr, 152 Ruoyu Rd, Wuhan 430079, Hubei, Peoples R China.;[Zhu, Yueying; Li, Wei; Cai, Xu] Cent China Normal Univ, Inst Particle Phys, 152 Ruoyu Rd, Wuhan 430079, Hubei, Peoples R China.;[Wang, Qiuping A.] HEI, Yncrea, F-59014 Lille, France.;[Li, Wei] Max Planck Inst Math Sci, Inselst 22, D-04103 Leipzig, Germany.
通讯机构：
[Zhu, Yueying] C;Cent China Normal Univ, Complex Sci Ctr, 152 Ruoyu Rd, Wuhan 430079, Hubei, Peoples R China.;Cent China Normal Univ, Inst Particle Phys, 152 Ruoyu Rd, Wuhan 430079, Hubei, Peoples R China.
关键词：
Uncertainty analysis;Sensitivity index;Correlation;Covariance;HIV model
摘要：
Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.
作者：
Su, Zhu;Deng, Weibing;Han, Jihui;Li, Wei;Cai, Xu
期刊：
Journal of Physics: Conference Series,2018年1113(1):012008 ISSN：1742-6588
通讯作者：
Su, Zhu(suz@mail.ccnu.edu.cn)
作者机构：
[Su, Zhu] National Engineering Laboratory for Technology of Big Data Applications in Education, Central China Normal University, Wuhan, China;[Han, Jihui] School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China;[Li, Wei; Deng, Weibing; Cai, Xu] Complexity Science Center, Institute of Particle Physics, Central China Normal University, Wuhan, China
通讯机构：
National Engineering Laboratory for Technology of Big Data Applications in Education, Central China Normal University, Wuhan, China
期刊：
Journal of Physics: Conference Series,2018年1113(1):012009 ISSN：1742-6588
作者机构：
Key Laboratory of Quark and Lepton Physics (MOE), Institute of Particle Physics, Central China Normal University, Wuhan, 430079, China;Commercial College, Shandong University, Weihai, Weihai, 264209, China
摘要：
Financial networks have become extremely useful in characterizing the structures of complex financial systems. Meanwhile, the time evolution property of the stock markets can be described by temporal networks. We utilize the temporal network framework to characterize the time-evolving correlation-based networks of stock markets. The market instability can be detected by the evolution of the topology structure of the financial networks. We then employ the temporal centrality as a portfolio selection tool. Those portfolios, which are composed of peripheral stocks with low temporal centrality scores, have consistently better performance under different portfolio optimization frameworks, suggesting that the temporal centrality measure can be used as new portfolio optimization and risk management tool. Our results reveal the importance of the temporal attributes of the stock markets, which should be taken serious consideration in real life applications. (C) 2018 Elsevier B.V. All rights reserved.
期刊：
Journal of Physics: Conference Series,2018年1113(1):012011 ISSN：1742-6588
作者机构：
School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China;Key Laboratory of Quark and Lepton Physics (MOE), Institute of Particle Physics, Central China Normal University, Wuhan, China
作者：
Yueying Zhu;Benwei Zhang;Qiuping A. Wang;Wei Li;Xu Cai
期刊：
Journal of Physics: Conference Series,2018年1113(1):012007 ISSN：1742-6588
作者机构：
Research Centre of Nonlinear Science, Wuhan Textile University, Wuhan, Hubei, 430073, China;Key Laboratory of Quark and Lepton Physics (MOE), Institute of Particle Physics, Central China Normal University, Wuhan, 430079, China;IMMM, UMR CNRS 6283, Le Mans Université, Le Mans, 72085, France;School of Hautes Etudes d'Ingenieur, Yncrea, Lille, 59014, France;Max-Planck Institute for Mathematics in the Sciences, Inselst. 22, Leipzig, 04103, Germany
作者机构：
[Deng, Shengfeng; Li, Wei] Huazhong Normal Univ, Coll Phys Sci & Technol, Wuhan 430079, Peoples R China.;[Li, Wei] Max Planck Inst Math Sci, D-04103 Leipzig, Germany.
通讯机构：
[Li, Wei] H;[Li, Wei] M;Huazhong Normal Univ, Coll Phys Sci & Technol, Wuhan 430079, Peoples R China.;Max Planck Inst Math Sci, D-04103 Leipzig, Germany.
摘要：
We study extensively the forget-remember mechanism (FRM) for message spreading, originally introduced in Eur. Phys. J. B 62, 247 (2008). The freedom of specifying forget-remember functions governing the FRM can enrich the spreading dynamics to a very large extent. The master equation is derived for describing the FRM dynamics. By applying the mean field techniques, we have shown how the steady states can be reached under certain conditions, which agrees well with the Monte Carlo simulations. The distributions of forget and remember times can be explicitly given when the forget-remember functions take linear or exponential forms, which might shed some light on understanding the temporal nature of diseases like flu. For time-dependent FRM there is an epidemic threshold related to the FRM parameters. We have proven that the mean field critical transmissibility for the SIS model and the critical transmissibility for the SIR model are the lower and the the upper bounds of the critical transmissibility for the FRM model, respectively.
期刊：
International Journal of Modern Physics C,2017年28(08):1750109 ISSN：0129-1831
通讯作者：
Zhu, Yueying
作者机构：
[Zhu, Yueying; Wang, Qiuping Alexandre] Le Mans Univ, IMMM, UMR CNRS 6283, F-72085 Le Mans, France.;[Zhu, Yueying; Li, Wei; Cai, Xu] Cent China Normal Univ, Complex Sci Ctr, Wuhan 430079, Hubei, Peoples R China.;[Zhu, Yueying; Li, Wei; Cai, Xu] Cent China Normal Univ, Inst Particle Phys, Wuhan 430079, Hubei, Peoples R China.;[Wang, Qiuping Alexandre] Yncrea, HEI, F-59014 Lille, France.;[Li, Wei] Max Planck Inst Math Sci, Inselst 22, D-04103 Leipzig, Germany.
通讯机构：
[Zhu, Yueying] L;[Zhu, Yueying] C;Le Mans Univ, IMMM, UMR CNRS 6283, F-72085 Le Mans, France.;Cent China Normal Univ, Complex Sci Ctr, Wuhan 430079, Hubei, Peoples R China.;Cent China Normal Univ, Inst Particle Phys, Wuhan 430079, Hubei, Peoples R China.
摘要：
In the complexity modeling, variance decomposition technique is widely used for the quantification of the variation in the output variables explained by covariates. In this work, the satisfaction of sampling-based variance decomposition strategy (SVDS) is firstly testified in the implementation of an analytic method for uncertainty and sensitivity analysis (UASA) of complex systems. Results suggest that SVDS may overvalue the impacts from individual covariates alone but underestimate the effects from their interactions when the model under discussion involves the interaction effects of nonlinear problems of individual covariates. Following the phenomenon, a modification of SVDS is proposed to generate sensitivity measures that well coincide with the analytic method. The testified strategy, together with our proposed modification, is then employed to clarify the roles of infectious rate and recovered rate, as well as of their interaction, in the estimation of equilibrium state (ES) for both SIR and SIS models. Results demonstrate that infectious and recovered rates almost play the same roles less crucial than that acted by the initial susceptible individuals in the decision of ES for SIR model, accompanied by a fragile contribution from their interactions; while in SIS model, infectious rate is more robust than recovered rate, and their interaction effect is also non-ignorable.
作者机构：
[Zou, Yijiang; Zhao, Longfeng; Deng, Weibing; Li, Wei; Su, Zhu; Han, Jihui; Han, JH; Li, W] Cent China Normal Univ, Complex Sci Ctr, Wuhan, Hubei, Peoples R China.;[Zou, Yijiang; Zhao, Longfeng; Deng, Weibing; Li, Wei; Su, Zhu; Han, Jihui; Han, JH; Li, W] Cent China Normal Univ, Inst Particle Phys, Wuhan, Hubei, Peoples R China.;[Han, Jihui] Zhengzhou Univ Light Ind, Sch Comp & Commun Engn, Zhengzhou, Henan, Peoples R China.
通讯机构：
[Han, JH; Li, W; Deng, WB] C;[Han, Jihui] Z;Cent China Normal Univ, Complex Sci Ctr, Wuhan, Hubei, Peoples R China.;Cent China Normal Univ, Inst Particle Phys, Wuhan, Hubei, Peoples R China.;Zhengzhou Univ Light Ind, Sch Comp & Commun Engn, Zhengzhou, Henan, Peoples R China.
关键词：
Community structure;Network analysis;Algorithms;Internet;Color codes;Food web structure;Neural networks;Metabolic networks
摘要：
An adaptive label propagation algorithm (ALPA) is proposed to detect and monitor communities in dynamic networks. Unlike the traditional methods by re-computing the whole community decomposition after each modification of the network, ALPA takes into account the information of historical communities and updates its solution according to the network modifications via a local label propagation process, which generally affects only a small portion of the network. This makes it respond to network changes at low computational cost. The effectiveness of ALPA has been tested on both synthetic and real-world networks, which shows that it can successfully identify and track dynamic communities. Moreover, ALPA could detect communities with high quality and accuracy compared to other methods. Therefore, being low-complexity and parameter-free, ALPA is a scalable and promising solution for some real-world applications of community detection in dynamic networks.
期刊：
Journal of Statistical Mechanics: Theory and Experiment,2017年2017(9):093401- ISSN：1742-5468
通讯作者：
Zhu, Yueying
作者机构：
[Zhu, Yueying; Wang, Qiuping Alexandre] Univ Maine, UMR CNRS 6283, IMMM, F-72085 Le Mans, France.;[Zhu, Yueying; Li, Wei; Cai, Xu] Cent China Normal Univ, Complex Sci Ctr, Wuhan 430079, Hubei, Peoples R China.;[Zhu, Yueying; Li, Wei; Cai, Xu] Cent China Normal Univ, Inst Particle Phys, Wuhan 430079, Hubei, Peoples R China.;[Wang, Qiuping Alexandre] Yncrea, HEI, F-59014 Lille, France.;[Li, Wei] Max Planck Inst Math Sci, Inselst 22, D-04103 Leipzig, Germany.
通讯机构：
[Zhu, Yueying] U;[Zhu, Yueying] C;Univ Maine, UMR CNRS 6283, IMMM, F-72085 Le Mans, France.;Cent China Normal Univ, Complex Sci Ctr, Wuhan 430079, Hubei, Peoples R China.;Cent China Normal Univ, Inst Particle Phys, Wuhan 430079, Hubei, Peoples R China.
关键词：
agent-based models;algorithmic game theory;evolutionary game theory;nonlinear dynamics