title: ELM Meets Urban Big Data Analysis: Case Studies.
abstract: In the latest years, the rapid progress of urban computing has engendered big issues, which creates both opportunities and challenges. The heterogeneous and big volume of data and the big difference between physical and virtual worlds have resulted in lots of problems in quickly solving practical problems in urban computing. In this paper, we propose a general application framework of ELM for urban computing. We present several real case studies of the framework like smog-related health hazard prediction and optimal retain store placement. Experiments involving urban data in China show the efficiency, accuracy, and flexibility of our proposed framework.
authors.affiliation: College of Computer Science and Technology, Zhejiang University, Zhejiang 310014, China.
authors.forename: Ningyu
authors.identifier: 0000-0002-1970-0678
authors.initials: N
authors.lastname: Zhang
authors.affiliation: Zhejiang University, Zhejiang, China.
authors.forename: Huajun
authors.initials: H
authors.lastname: Chen
authors.affiliation: Zhejiang University, Zhejiang, China.
authors.forename: Xi
authors.identifier: 0000-0003-0883-0124
authors.initials: X
authors.lastname: Chen
authors.affiliation: Zhejiang University, Zhejiang, China.
authors.forename: Jiaoyan
authors.initials: J
authors.lastname: Chen