Earticle

초록

영어

As cities in developing countries are expanding rapidly in recent years, flood has an increasing impact on urban management. In this paper, we present the design and implementation of an urban flood defense decision support system based on big data. The system connects real-time sensor to collect streaming data, and uses a data-driven method that considers temporal and spatial factors to forecast water level in the next 6 hours. Thus, it can provide enough time for the authorities to take pertinent flood protection measures such as evacuation. Our predictive model is a hybrid of linear regression and artificial neural network, and can give early warning of potential flood using the forecast results. The system is implemented on Java EE platform, and integrated with Baidu Maps API to provide a user-friendly interface.

목차

Abstract
 1. Introduction
 2. 2. Overview of System
  2.1. Framework of the System
  2.2. Website Architecture
 3. System Implementation
  3.1. Database Design
  3.2. Geographical Display with Baidu Maps
  3.3. Visual Analytics
  3.4. Framework of the Predictive Model
  3.5. Forecast and Warning
 4. Conclusions
 References

키워드

저자

• Taimeng Yang [ School of Computer and Computing Science, Zhejiang University City College, Hangzhou, 310015, P.R. China, College of Computer Science, Zhejiang University, Hangzhou, 310027, P.R. China ]
• Guanlin Chen [ School of Computer and Computing Science, Zhejiang University City College, Hangzhou, 310015, P.R. China, College of Computer Science, Zhejiang University, Hangzhou, 310027, P.R. China ] Corresponding author
• Xinxin Sun [ Department of Computer Science and Information, Zhejiang University of Water Conservancy and Electric Power, Hangzhou, 310018, P.R. China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605