Detecting fraud via statistical anomalies

Urban planners and researchers are increasingly integrating mobility data in designing smarter and sustainable cities. It is therefore crucial to identify any anomalies in the dataset to prevent poor planning or statistical interferences. Such mobility data could come from public sources or data b...

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Bibliographic Details
Main Author: Lee, Cara Zheng Yan
Other Authors: Fedor Duzhin
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/175633