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Comparing the Performance of Different Artificial Intelligence Based Clustering Algorithms in Healthcare Waste Disposal Location

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Author
Gergin, Zeynep
Esnaf, Şakir
Type
conferenceObject
Date
2013-08
Language
en_US
Metadata
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Abstract
In this study four different clustering algorithms are compared with respect to their cost performance for a real world multi facility location problem. First two algorithms are Fuzzy C-Means and Self Organizing Maps. Then, these algorithms are integrated with Center of Gravity Method, named as FCM-COG and SOM-COG. All algorithms are applied to a multi facility location problem for clustering geographical coordinate data of Istanbul hospitals, to serve Istanbul Metropolitan Municipality Environmental Management Industrial and Trade Inc. (ISTAÇ) in its medical waste management activities. ISTAÇ will use the results to identify the alternative places of sterilization facilities, and reducing the distance that hazardous wastes are transferred. Clustering is performed for different number of clusters predefined by ISTAÇ, and results are compared with respect to CPU time performance, and total cost which is defined as the amount of waste produced by a hospital, multiplied by its distance to the sterilization facility.
Subject
Fuzzy C-Means
Self Organizing Maps
Center of Gravity
Healthcare waste disposal location
URI
https://hdl.handle.net/11413/3058
Collections
  • Bildiriler, Kongreler ve Sempozyumlar / Declarations, Congresses and Symposiums [59]

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İstanbul Kültür University

Hakkında |Politika | Kütüphane | İletişim | Send Feedback | Admin

Istanbul Kültür University, Ataköy Campus E5 Karayolu Üzeri Bakırköy 34158, İstanbul / TURKEY
Copyright © İstanbul Kültür University

Creative Commons Lisansı
IKU Institutional Repository, Creative Commons Alıntı-GayriTicari-Türetilemez 4.0 Uluslararası Lisansı ile lisanslanmıştır.

Designed by  UNIREPOS