Keynote Speakers

 

 

Prof. Philippe Fournier-Viger, Shenzhen University (China)

Philippe Fournier-Viger (Ph.D) is a Canadian researcher, distinguished professor at Shenzhen University (China). Five years after completing his Ph.D., he came to China and became full professor at the Harbin Institute of Technology (Shenzhen), after obtaining a title of national talent from the National Science Foundation of China. He has published more than 350 research papers related to data mining, intelligent systems and applications, which have received more than 10,000 citations (H-Index 51). He is editor-in-chief of Data Science and Pattern Recognition and former associate editor-in-chief of the Applied Intelligence journal (SCI, Q1). He is the founder of the popular SPMF data mining library, offering more than 230 algorithms, cited in more than 1,000 research papers. He is a co-founder of the UDML, PMDB and MLiSE series of workshops held at the ICDM, PKDD and KDD conferences. Website: http://www.philippe-fournier-viger.com
 

 

Prof. Lili Yang, Southern University of Science and Technology, China

Prof. Dr Lili Yang is working in Southern University of Science and Technology in Shenzhen, China. She is also a reader in the School of Business and Economics at Loughborough University, UK. She has conducted a significant amount of research both independently and working in team. As the principal investigator she has led 14 projects and carried out 6 projects as co-investigator. The total budget has reached to over £5 million. Her recent publications appear in the top journals such as Applied Energy, Information Systems Research, European Journal of Operational Research, Technological Forecasting and Social Changes, to be named. She was invited by the UK Cabinet Office and gave a presentation to their staff in London. Her research has generated impact to the research community in the whole world.

 

Title: Shortest Path Planning and Dynamic Rescue Forces Dispatching for Urban Waterlog Disasters

Abstract: An urban waterlog disaster can pose a serious threat to human life and property safety. This paper makes shortest path planning and dynamic scheduling of rescue forces, mainly about firefighters and fire engines, for urban waterlog disasters triggered by short-term intensive rainfall. A two-step approach is proposed. The first step is to acquire the optimal travel times from fire stations to local flooding sites under the extension of floods. A path selection model has been created for rescue vehicles in times of floods. A customized A* algorithm is developed to solve the model with a high search efficiency. Additionally, a preference-based customized A* algorithm is designed to select paths for which users’ preferences is considered. The second step is to make dynamic dispatching of rescue forces to flooding sites. The demand for firefighters at each flooding site is estimated based on the population density and the detected real-time waterlog depths. The optimal travel times obtained in the first step are used as input in a bi-objective dynamic dispatching model. A case study in Futian District of Shenzhen, China is presented to demonstrate the practicability of our rescue planning. This study has been financially supported by National Key Project, which has built an emergency rescue system for urban waterlog disasters, providing quick auxiliary decision support for decision-makers.