Opening book details…
Can I read Big Data of Urban Waterlogging Public Opinion Monitoring and Early Warning Method Detection on EtoBox?
Big Data of Urban Waterlogging Public Opinion Monitoring and Early Warning Method Detection by Haibo Yang; Youkun Wang; Nasser Jaber is a book available to read on EtoBox.
What is Big Data of Urban Waterlogging Public Opinion Monitoring and Early Warning Method Detection about?
The occurrence of waterlogging disaster has brought great economic losses to the society and brought great threats to the safety of the city, people's lives and the sustainable development of the society. Use big data technology to dynamically monitor urban waterlogging network public opinion, use data mining and other data mining technology, real-time collection of urban waterlogging public opinion data, deeply analyze the evolution trend of public opinion heat, focus on key points and emotional tendency. Taking the sample of the July 16 flood event in Beijing, this paper studies the transmission characteristics of urban waterlogging events and reveals the dynamic mechanism of its development. It is found that there is a significant positive correlation between the high incidence period of urban waterlogging disasters and the heat of public opinion and its impact level on waterlogging events. The social attention to the waterlogging problem mainly focuses on the construction of the drainage system, the progress of the waterlogging disaster and the disaster relief work. The development process of public opinion in urban waterlogging events has gone through five periods: incubation
- Author
- Haibo Yang; Youkun Wang; Nasser Jaber
- Publisher
- Springer Nature Singapore Pte Ltd Fka Springer Science + Business Media Singapore Pte Ltd
- Published
- 2023
- Language
- EN
- ISBN
- 9789811993756
- Subjects
- Mathematics, Engineering, Science
More by Haibo Yang; Youkun Wang; Nasser Jaber
Browse all works by Haibo Yang; Youkun Wang; Nasser Jaber
Similar books
- Anomaly Detection and Complex Event Processing Over IoT Data Streams : With Application to EHealth and Patient Data Monitoring — Patrick Schneider; Fatos Xhafa (2022)
- Collection and Consolidation of Big Data for Proactive Monitoring of Critical Events at Infrastructure Facilities in an Urban Environment — Anton Finogeev; Danila Parygin; Sergey Schevchenko; Alexey Finogeev; Danish Ather (2021)
- Fast Hoeffding Drift Detection Method for Evolving Data Streams — Ali Pesaranghader; Herna L. Viktor (2016)
- Deep Learning in Big Data and Data Mining — Deepak Kumar Sharma; Bhanu Tokas; Leo Adlakha (2021)
- Big Data and AI — Shuya Hayashi; Koki Arai (2024)
- The Impact of AI: Interpretations from Public Opinion and Industry Frameworks — Herlander Elias (2024)