Predicting urban flooding susceptibility of public transit systems using machine learning approaches: a case study of the largest city in Canada.
Naser AhmedJinhyung LeePublished in: ARIC@SIGSPATIAL (2021)
Keyphrases
- machine learning approaches
- machine learning methods
- public transportation
- distributed systems
- machine learning algorithms
- case study
- computer systems
- urban areas
- machine learning
- machine learning models
- public space
- data mining methods
- complex systems
- retrieval systems
- united states
- intelligent systems
- artificial intelligence
- united kingdom
- databases