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JACIII Vol.18 No.4 pp. 538-548
doi: 10.20965/jaciii.2014.p0538
(2014)

Paper:

Fuzzy Cognitive Maps and Bacterial Evolutionary Algorithm Approach to Integrated Waste Management Systems

Adrienn Buruzs*, Miklós Ferenc Hatwágner**,
and László Tamás Kóczy***

*Department of Environmental Engineering Széchenyi István University, Gyõr, Egyetem tér 1., Hungary

**Department of Information Technology Széchenyi István University, Gyõr, Egyetem tér 1., Hungary

***Department of Telecommunications and Media Informatics Budapest University of Technology and Economics, Budapest, Magyar tudósok körútja 2., Hungary

Received:
February 3, 2014
Accepted:
April 30, 2014
Published:
July 20, 2014
Keywords:
integrated waste management system, sustainability factors, fuzzy cognitive map, bacterial evolutionary algorithm, optimization
Abstract

Sustainable waste management systems necessarily include many interacting factors. Due to the complexity and uncertainties occurring in sustainable waste management systems, we propose the use of Fuzzy Cognitive Maps (FCM) and Bacterial Evolutionary Algorithm (BEA) [1] to support the planning and decision making process of integrated systems, as the combination of methods FCM and BEA seems to be suitable to model such complex mechanisms as Integrated Waste Management Systems (IWMS). This paper is an attempt to assess the sustainability of the IWMS in a holistic approach. While the FCM model represents the IWMS as a whole, the BEA is used for parameter optimization and identification. An interpretation of the results obtained by the FCM for the actual regional IWMS is also presented. We have obtained some surprising results, contradicting the general assumptions in the literature concerning the relative importance of constituting components in waste management systems.

Cite this article as:
A. Buruzs, M. Hatwágner, and <. Kóczy, “Fuzzy Cognitive Maps and Bacterial Evolutionary Algorithm Approach to Integrated Waste Management Systems,” J. Adv. Comput. Intell. Intell. Inform., Vol.18, No.4, pp. 538-548, 2014.
Data files:
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Last updated on Nov. 12, 2018