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Nanjing, China

Gong P.F.,Jiangsu Police Institute
Material Science and Environmental Engineering - Proceedings of the 3rd annual 2015 International Conference on Material Science and Environmental Engineering, ICMSEE 2015 | Year: 2016

In order to overcome the negative effect on the urban road traffic system effectively, it is necessary to determine the urban road traffic early warning level and take some appropriate emergency management measures when adverse weather occurs in urban area. Based on the traffic impact analysis of urban road traffic system in adverse weather conditions, this paper presents a four-level urban road traffic early warning classification method in accordance with the early warning level of the adverse weather and its temporal-spatial distribution characteristics. The classification method refers to the risk matrix, which is a kind of popular evaluation method in the emergency management field because of its simplicity and adaptability. The present work may be very useful for decision-makers and practitioners trying to determine the urban road traffic early warning levels in adverse weather conditions. © 2016 Taylor and Francis Group, London. Source


Zhang L.,Jiangsu Police Institute | Wu B.-Y.,Xiamen University
Environment, Energy and Sustainable Development - Proceedings of the 2013 International Conference on Frontier of Energy and Environment Engineering, ICFEEE 2013 | Year: 2014

As an emerging industry, tourism industry's development has formed a certain scale in China; the impact on China's economic growth has become increasingly stronger. In this paper, we use the macro-economic data from 1999 to 2008 to make an empirical test on the effect of tourism industry on economic growth in central China by Cobb-Douglas production function and panel data model. The basic conclusion is: from the analysis of fixed effects model, tourism industry drives economic growth not only through its own direct income effect, but more importantly, because of its association with the industry, it expands economic growth effects through the multiplier effect, and give a strong impetus to the six provinces in central China which have rich tourism resources. © 2014 Taylor & Francis Group, London. Source


Yang Y.,Hohai University | Yang L.,Zhejiang Institute of Hydrogeology and Engineering Geology | Cai D.,Jiangsu Police Institute
Proceedings - International Conference on Natural Computation | Year: 2016

The optimal design of groundwater remediation systems are often subject to uncertain hydrogeological parameters and multiple uncertain objectives, involving minimization of remediation cost, and minimization of contaminant mass remaining in the aquifer. To design a robust and reliable groundwater remediation system, the stochastic simulations (Monte Carlo simulation) with multiple realizations of uncertain parameters, which are generated by Sequential Gaussian Simulation (SGSIM), are applied to tackle the uncertainty analysis of an synthetic remediation site. In the present study, we propose a probabilistic multi-objective evolutionary algorithm, named probabilistic improved niched Pareto genetic algorithm (PINPGA). PINPGA was improved by using stochastic simulation for objection function evaluations and incorporating probabilistic Pareto ranking and niche technique into INPGA for multi-objective selection operator. The proposed algorithm is then applied to the synthetic groundwater remediation test case. The performances of the methodology generating the reliability of the Pareto-optimal solution are assessed and compared using Monte Carlo analysis. The optimization results indicate that using such an uncertainty-based multi-objective optimization scheme can give reliable solution to groundwater remediation design, giving decision makers a practical and robust optimization tool. © 2015 IEEE. Source


Zhang L.,Jiangsu Police Institute
Green Building, Materials and Civil Engineering - Proceedings of the 4th International Conference on GreenBuilding, Materials and Civil Engineering, GBMCE 2014 | Year: 2015

Based on the panel data from 2000 to 2011 of 41 developing countries, this paper discusses the influence factors of income payment in sub-project of current account perspective. It find that the per capita GDP, foreign direct investment, the profit from foreign direct investment, employee compensation and carbon emissions have significantly positive correlation to income payment, while the power consumption amount and population density on the significant negative correlation relationship. The paper also analyses the residual graph from cross section. © 2015 Taylor & Francis Group, London. Source


Cai D.,Jiangsu Police Institute | Chen Y.M.,Nanjing University | Gao C.,Key Laboratory of Geographic Information Technology of Public Security Ministry
Communications in Computer and Information Science | Year: 2016

Geo-Informatic Tupu is a complex spatio-temporal analysis method. Its detailed, simple image analysis and expression ways can be better meet the crime spatio-temporal analysis needs. This paper summarizes the research background and current situation of crime spatio-temporal analysis, and discusses the significance and content of this research. And also this paper puts forward own ideas about research ways, which is in order to provide a new method for method references and decision supports in the crime spatio-temporal analysis practices. © Springer-Verlag Berlin Heidelberg 2016. Source

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