Author:
Buruzs Adrienn, ,Hatwágner Miklós Ferenc,Kóczy László Tamás, ,
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.
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
Reference45 articles.
1. W. Stach, L. Kurgan, W. Pedrycz, and M. Reformat, “Genetic Learning of Fuzzy Cognitive Maps,” Fuzzy Sets and Systems, Vol.153, pp. 371-401, 2005.
2. Council Directive 1999/31/EC of 26 April 1999 on the landfill of waste.
3. European Parliament and Council Directive 94/62/EC of 20 December 1994 on packaging and packaging waste.
4. P. S. Phillips, A. D. Read, A. E. Green, and M. P. Bates, “UK waste minimisation clubs: a contribution to sustainable waste management,” Resources, Conservation and Recycling, Vol.27, pp. 217-247, 1999.
5. A. Demirbas, “Waste Management, Waste Resource Facilities and Waste Conversion Processes,” Energy Conservation and Management, 52, 1280-1287, 2011.
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献