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        • SCOPUSKCI등재

          Weighted Local Naive Bayes Link Prediction

          Wu, JieHua,Zhang, GuoJi,Ren, YaZhou,Zhang, XiaYan,Yang, Qiao Korea Information Processing Society 2017 Journal of information processing systems Vol.13 No.4

          Weighted network link prediction is a challenge issue in complex network analysis. Unsupervised methods based on local structure are widely used to handle the predictive task. However, the results are still far from satisfied as major literatures neglect two important points: common neighbors produce different influence on potential links; weighted values associated with links in local structure are also different. In this paper, we adapt an effective link prediction model-local naive Bayes model into a weighted scenario to address this issue. Correspondingly, we propose a weighted local naive Bayes (WLNB) probabilistic link prediction framework. The main contribution here is that a weighted cluster coefficient has been incorporated, allowing our model to inference the weighted contribution in the predicting stage. In addition, WLNB can extensively be applied to several classic similarity metrics. We evaluate WLNB on different kinds of real-world weighted datasets. Experimental results show that our proposed approach performs better (by AUC and Prec) than several alternative methods for link prediction in weighted complex networks.

        • KCI등재

          Moderating effect of regulatory focus on public acceptance of nuclear energy

          Yanling He,Yazhou Li,Dongqin Xia,Tingting Zhang,Yongliang Wang,Li Hu,Jibao Gu,Yican Wu 한국원자력학회 2019 Nuclear Engineering and Technology Vol.51 No.8

          Public acceptance has become the most critical question for sustainable development of nuclear energy in recent decades. Many researches concentrated on risk and benefit perception, which were deemed as the most influential factors of Public Acceptance of Nuclear Energy (PANE). But few researches focused on psychological factors including regulatory focus. Therefore, this paper aimed to explore the moderating effect of regulatory focus on PANE based on Regulatory Focus Theory in order to find ways to increase/decrease PANE. An Internet-based survey had been carried out in China nationwide. The results indicated that trust in government was positively related to PANE and this relationship was mediated by risk and benefit perception. In addition, the strength of the associations between risk and benefit perception and PANE were moderated by regulatory focus, consisting of prevention focus and promotion focus. Pre-vention focus strengthened the negative relationship between risk perception and PANE, while pro-motion focus weakened. Moreover, promotion focus weakened the positive relationship between benefit perception and PANE, but no significant moderating effect of prevention focus was founded on the relationship between benefit perception and PANE. Some policy implications were also proposed on the basis of above-mentioned findings.

        • SCOPUS
        • KCI등재

          Weighted Local Naive Bayes Link Prediction

          ( Jiehua Wu ),( Guoji Zhang ),( Yazhou Ren ),( Xiayan Zhang ),( Qiao Yang ) 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.4

          Weighted network link prediction is a challenge issue in complex network analysis. Unsupervised methods based on local structure are widely used to handle the predictive task. However, the results are still far from satisfied as major literatures neglect two important points: common neighbors produce different influence on potential links; weighted values associated with links in local structure are also different. In this paper, we adapt an effective link prediction model―local naive Bayes model into a weighted scenario to address this issue. Correspondingly, we propose a weighted local naive Bayes (WLNB) probabilistic link prediction framework. The main contribution here is that a weighted cluster coefficient has been incorporated, allowing our model to inference the weighted contribution in the predicting stage. In addition, WLNB can extensively be applied to several classic similarity metrics. We evaluate WLNB on different kinds of real-world weighted datasets. Experimental results show that our proposed approach performs better (by AUC and Prec) than several alternative methods for link prediction in weighted complex networks.

        • SCIESCOPUSKCI등재

          Moderating effect of regulatory focus on public acceptance of nuclear energy

          He, Yanling,Li, Yazhou,Xia, Dongqin,Zhang, Tingting,Wang, Yongliang,Hu, Li,Gu, Jibao,Wu, Yican Korean Nuclear Society 2019 Nuclear Engineering and Technology Vol.51 No.8

          Public acceptance has become the most critical question for sustainable development of nuclear energy in recent decades. Many researches concentrated on risk and benefit perception, which were deemed as the most influential factors of Public Acceptance of Nuclear Energy (PANE). But few researches focused on psychological factors including regulatory focus. Therefore, this paper aimed to explore the moderating effect of regulatory focus on PANE based on Regulatory Focus Theory in order to find ways to increase/decrease PANE. An Internet-based survey had been carried out in China nationwide. The results indicated that trust in government was positively related to PANE and this relationship was mediated by risk and benefit perception. In addition, the strength of the associations between risk and benefit perception and PANE were moderated by regulatory focus, consisting of prevention focus and promotion focus. Prevention focus strengthened the negative relationship between risk perception and PANE, while promotion focus weakened. Moreover, promotion focus weakened the positive relationship between benefit perception and PANE, but no significant moderating effect of prevention focus was founded on the relationship between benefit perception and PANE. Some policy implications were also proposed on the basis of above-mentioned findings.

        • Nonlinear electromechanical dynamics of piezoelectric doubly-curved microsystem using modified strain gradient theory

          Wang, Dongxuan,Xing, Yazhou,Zhang, Su Techno-Press 2021 Advances in nano research Vol.11 No.4

          This paper is devoted to investigate the nonlinear free vibrations of multi-phase piezoelectric doubly-curved microshells in the context of modified strain gradient elastic (MSGT). The microshell has been made from two constituents for which different compositions have been considered by defining a piezoelectric phase percentage. The microscale effects have been described with the incorporation of three scale coefficients involved in MSGT. With the use of suitable Fourier series and the concept of Galerkin's method, the solution for the governing equations of double-curvature microshell have been provided. The calculated frequencies are dependent on the piezoelectric phase percentage, scale coefficients, curvature radius and applied electric voltage.

        • KCI등재

          Feasibility study of improved particle swarm optimization in kriging metamodel based structural model updating

          Yun-Lai Zhou,Shiqiang Qin,Jia Hu,Yazhou Zhang,Juntao Kang 국제구조공학회 2019 Structural Engineering and Mechanics, An Int'l Jou Vol.70 No.5

          This study proposed an improved particle swarm optimization (IPSO) method ensemble with kriging model for model updating. By introducing genetic algorithm (GA) and grouping strategy together with elite selection into standard particle optimization (PSO), the IPSO is obtained. Kriging metamodel serves for predicting the structural responses to avoid complex computation via finite element model. The combination of IPSO and kriging model shall provide more accurate searching results and obtain global optimal solution for model updating compared with the PSO, Simulate Annealing PSO (SimuAPSO), BreedPSO and PSOGA. A plane truss structure and ASCE Benchmark frame structure are adopted to verify the proposed approach. The results indicated that the hybrid of kriging model and IPSO could serve for model updating effectively and efficiently. The updating results further illustrated that IPSO can provide superior convergent solutions compared with PSO, SimuAPSO, BreedPSO and PSOGA.

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