Haitao Sun, Zhiru Wang, Guofeng Su, & Jianguo Chen. (2016). Topological Structure Vulnerability Assessment of Shanghai Urban Metro Networks. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Topological structure vulnerability assessment approach for Urban Metro Networks (UMNS) was proposed in order to decrease the impact caused by incidents. Failure scale of stations and sections random failure and target attacks was evaluated. The results show that UMNS is more vulnerable to target attacks on stations than random failure on stations. But UMNS is less vulnerable to target attacks on sections than random failure on sections. Additionally, UMNS is more vulnerable to station failure than sections. It could be concluded as more resources should be put on big transfer stations in UMNS operation management to avoid large scale impacts. The proposed methodology is not intended to predict the occurrence of events but rather to be used a management tool. Results from the evaluation are valuable elements in planning UMNS. They can be used for network planning, further detailed hazard studies, deciding on the arrangement of emergency resources.
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Lida Huang, Guoray Cai, Hongyong Yuan, Jianguo Chen, Yan Wang, & Feng Sun. (2018). Modeling Threats of Mass Incidents Using Scenario-based Bayesian Network Reasoning. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 121–134). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Mass incidents represent a global problem, putting potential threats to public safety. Due to the complexity and uncertainties of mass incidents, law enforcement agencies lack analytical models and structured processes for anticipating potential threats. To address such challenge, this paper presents a threat analysis framework combining the scenario analysis method and Bayesian network (BN) reasoning. Based on a case library
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Peng Du, Jianguo Chen, & Zhanhui Sun. (2016). Resource Management System for Crisis Response & Management. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Crisis response and management is a critical duty of authorities worldwide to ensure the wellbeing and safety of their citizens and the sustenance and function of society. One of the core components of crisis response is the management of various resources that support the emergency response operations. In this paper, the design of an emergency resource management system is presented, which is developed to utilise geographic information system (GIS), internet of things (IoT), and cloud technologies for precise and real-time inventory management as well as dynamic and adaptive resource dispatching services.
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Yiting Zheng, Jianguo Chen, Wenjie Tang, & Jiaxiang Xu. (2016). Research on Target Diversity and Risk Analysis Model of Terrorist Attack. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Terrorist attack continues to spread in the world which leads to severe casualties and property losses and poses great pressure to the government. Therefore it is essential to identify the potential targets terrorists may select, assess the risk level and take risk management measures in advance. Aiming to this problem, the paper provides a new analysis method. Firstly it investigates target types terrorists prefer to and target diversity based on the data in Global Terrorist Database ; Then it puts forward the target risk analysis of three-dimensional model which considers the threat probabilityã?the target vulnerability and the consequence severity; Finally, the paper calculates and assesses the risk level using the fuzzy synthesis decision-making method, and two examples are given to prove the feasibility of the model. The result can contribute to target risk analysis and emergency preparedness or management of terrorist attack.
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Binxu Zhai, & Jianguo Chen. (2017). Research on the forecasting of Air Quality Index (AQI) based on FS-GA-BPNN: A case study of Beijing, China. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 307–321). Albi, France: Iscram.
Abstract: The analysis and forecasting of eminent air quality play a significant role in municipal regulatory planning and emergency preparedness. In this paper, a FS-GA-BPNN model forecasting the daily average Air Quality Index (AQI) is proposed. Special procedures for feature extraction to find more potential significant variables and feature selection to remove redundant information and avoid overfitting are conducted before modelling. Three different models – BPNN, GA-BPNN and FS-GA-BPNN are established to compare the prediction accuracy, generalization ability and reliability. 17 parameters involving pollutant concentration, meteorological elements and surrounding factors are found essential for the method effectiveness. The result shows that the FS-GA-BPNN model generally performs superior to ordinary BPNN, suggesting the necessity of extensive data mining and feature extraction for successful machine learning. The results of this paper can help to conduct air quality pre-warning system and improve the emergency planning process of extreme weather events.
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Xiujuan Zhao, Jianguo Chen, Peng Du, Wei Xu, Ran Liu, & Hongyong Yuan. (2019). Location-allocation model for earthquake shelter solved using MPSO algorithm. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Constructing shelters in suitable quantities, with adequate capacities and at the right locations is essential for evacuees under earthquake disasters. As one of the disaster management methods, constructing shelters can help to significantly reduce disruption and devastation to affected population. Mathematical models have been used to solve this problem allied with a heuristic optimization algorithm. The optimization of evacuation efficiency, as one of the most important objectives, has many expressive forms, such as minimizing evacuation distance and evacuation time. This paper proposes a new model that aims to minimize evacuation time with a new calculation method and to maximize total evacuees? comfort level. The modified particle swarm optimization (MPSO) algorithm is employed to solve the model and the result is compared with a model that calculated evacuation time differently and a model without distance constraint, respectively.
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