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June 4, 2026Journal of Ambient Intelligence and Humanized ComputingOpen Access

A novel fuzzy clustering urban hot spot detection method—an application in crime analysis

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Authors

RCRosa CafaroBCBarbara CardoneFMFerdinando Di Martino

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Overview

Randomized trial demonstrates improved hotspot detection in urban areas, suggesting enhanced analytical tools.

Key Points

  • The aim is to enhance the accuracy of urban hotspot detection methods using an improved Fuzzy C-means algorithm.
  • Developed a weighted Fuzzy C-means algorithm to evaluate data point density.
  • Conducted experimental tests on crime events from 2019 to 2024 in the District of Columbia.
  • Assessed robustness to noise and ability to capture overlapping hotspots.
  • Improved performance of Fuzzy C-means-based detection algorithms noted.
  • Successfully detected intersecting and elongated hotspots.
  • Provided valid tools for localization and analysis of urban hotspot evolution.

Cite This Study

Cafaro et al. (2026) studied this question.

synapsesocial.com/papers/6a21171dd499ed480b170082https://doi.org/10.1007/s12652-026-05096-1
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