NDLI: The Multiple Pheromone Ant Clustering Algorithm and its application to real world domains

Content Provider	IEEE Xplore Digital Library
Author	Chircop, J. Buckingham, C.D.
Copyright Year	2013
Description	Author affiliation: Aston Univ., Birmingham, UK (Chircop, J.; Buckingham, C.D.)
Abstract	The Multiple Pheromone Ant Clustering Algorithm (MPACA) models the collective behaviour of ants to find clusters in data and to assign objects to the most appropriate class. It is an ant colony optimisation approach that uses pheromones to mark paths linking objects that are similar and potentially members of the same cluster or class. Its novelty is in the way it uses separate pheromones for each descriptive attribute of the object rather than a single pheromone representing the whole object. Ants that encounter other ants frequently enough can combine the attribute values they are detecting, which enables the MPACA to learn influential variable interactions. This paper applies the model to real-world data from two domains. One is logistics, focusing on resource allocation rather than the more traditional vehicle-routing problem. The other is mental-health risk assessment. The task for the MPACA in each domain was to predict class membership where the classes for the logistics domain were the levels of demand on haulage company resources and the mental-health classes were levels of suicide risk. Results on these noisy real-world data were promising, demonstrating the ability of the MPACA to find patterns in the data with accuracy comparable to more traditional linear regression models.
Starting Page	27
Ending Page	34
File Size	271163
Page Count	8
File Format	PDF
ISBN	9788360810521
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-08
Publisher Place	Poland
Access Restriction	Subscribed
Rights Holder	Polish Information Processing Society
Subject Keyword	Computational modeling Sociology Clustering algorithms Data models Statistics Standards Logistics
Content Type	Text
Resource Type	Article

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