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Fuzzy geographically weighted clustering using artificial bee colony: An efficient geo-demographic analysis algorithm and applications to the analysis of crime behavior in population

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Abstract

Geo-demographic analysis is an essential part of a geographical information system (GIS) for predicting people’s behavior based on statistical models and their residential location. Fuzzy Geographically Weighted Clustering (FGWC) serves as one of the most efficient algorithms in geo-demographic analysis. Despite being an effective algorithm, FGWC is sensitive to initialize when the random selection of cluster centers makes the iterative process falling into the local optimal solution easily. Artificial Bee Colony (ABC), one of the most popular meta-heuristic algorithms, can be regarded as the tool to achieve global optimization solutions. This research aims to propose a novel geo-demographic analysis algorithm that integrates FGWC to the optimization scheme of ABC for improving geo-demographic clustering accuracy. Experimental results on various datasets show that the clustering quality of the proposed algorithm called FGWC-ABC is better than those of other relevant methods. The proposed algorithm is also applied to a decision-making application for analyzing crime behavior problem in the population using the US communities and crime dataset. It provides fuzzy rules to determine the violent crime rate in terms of linguistic labels from socioeconomic variables. These results are significant to make predictions of further US violent crime rate and to facilitate appropriate decisions on prevention such the situations in the future.

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Acknowledgments

The authors are greatly indebted to the editor-in-chief, Prof. Moonis Ali; anonymous reviewers for their comments and their valuable suggestions that improved the quality and clarity of paper. The authors wish to give special thanks to Mr. Nguyen Tho Thong, VNU for suggestion on experimental simulation of this work. This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 102.05-2014.01.

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Authors and Affiliations

  1. School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Jl. Ganesha 10, Bandung, Indonesia

    Arie Wahyu Wijayanto & Ayu Purwarianti

  2. VNU University of Science, Vietnam National University, 334 Nguyen Trai, Thanh Xuan, Hanoi, Vietnam

    Le Hoang Son

Authors
  1. Arie Wahyu Wijayanto
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  2. Ayu Purwarianti
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  3. Le Hoang Son
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Correspondence to Le Hoang Son.

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Wijayanto, A.W., Purwarianti, A. & Son, L.H. Fuzzy geographically weighted clustering using artificial bee colony: An efficient geo-demographic analysis algorithm and applications to the analysis of crime behavior in population. Appl Intell 44, 377–398 (2016). https://doi.org/10.1007/s10489-015-0705-7

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