Expert Based System Design for Integrated Waste Management
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33093
Expert Based System Design for Integrated Waste Management

Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

Abstract:

Recently, an increasing number of researchers have been focusing on working out realistic solutions to sustainability problems. As sustainability issues gain higher importance for organisations, the management of such decisions becomes critical. Knowledge representation is a fundamental issue of complex knowledge based systems. Many types of sustainability problems would benefit from models based on experts’ knowledge. Cognitive maps have been used for analyzing and aiding decision making. A cognitive map can be made of almost any system or problem. A fuzzy cognitive map (FCM) can successfully represent knowledge and human experience, introducing concepts to represent the essential elements and the cause and effect relationships among the concepts to model the behaviour of any system. Integrated waste management systems (IWMS) are complex systems that can be decomposed to non-related and related subsystems and elements, where many factors have to be taken into consideration that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall decision process of the system. The goal of the present paper is to construct an efficient IWMS which considers various factors. The authors’ intention is to propose an expert based system design approach for implementing expert decision support in the area of IWMSs and introduces an appropriate methodology for the development and analysis of group FCM. A framework for such a methodology consisting of the development and application phases is presented.

Keywords: Factors, fuzzy cognitive map, group decision, integrated waste management system.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1097008

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1962

References:


[1] M. S. Khan, M., Quaddus, Group Decision Support Using Fuzzy Cognitive Maps for Causal Reasoning, Group Decision and Negotiation, September 2004, Volume 13, Issue 5, pp 463-480.
[2] U. Özesmi, S. L. Özesmi, Ecological models based on people’s knowledge: a multi-step fuzzy cognitive mapping approach, Ecological Modelling, Volume 176, Issues 1–2, 15 August 2004, Pages 43–64.
[3] M. K. Ketipi, D. E. Koulouriotis, E. G. Karakasis, G. A. Papakostas, V. D. Tourassis, A flexible nonlinear approach to represent cause–effect relationships in FCMs, Applied Soft Computing, Volume 12, Issue 12, December 2012, Pages 3757–3770.
[4] G. Xirogiannisa, J. Stefanoua, M. Glykasb, A fuzzy cognitive map approach to support urban design, Expert Systems with Applications, Volume 26, Issue 2, February 2004, Pages 257–268.
[5] Özesmi, U. and Özesmi, S. L. (2004). Ecological Models Based on People’s Knowledge: a Multi-step Fuzzy Cognitive Mapping Approach. J. of Ecological Modelling, 176(15): 3–64.
[6] Hung, M-L., Ma, H-w. and Yang W-F. (2007). A Novel Sustainable Decision Making Model for Municipal Solid Waste Management. J. of Waste Management, 27(2): 209–219.
[7] Papageorgiou, E. and Kontogianni, A. (2012). Using Fuzzy Cognitive Mapping in Environmental Decision Making and Management: A Methodological Primer and an Application. Int. Perspectives on Global Environmental Change, S. Young (ed.), ISBN: 978-953-307-815-1, InTech, doi: 10.5772/29375.
[8] Salhofer, S., Wassermann, G. and Binner, E. (2007). Strategic Environmental Assessment as an Approach to Assess Waste Management Systems. Experiences from an Austrian Case Study. J. of Environmental Modelling & Software, 22(5): 610–618.
[9] Tanskanen, J-H. (2000). Strategic Planning of Municipal Solid Waste Management. J. of Resources, Conservation and Recycling 30(2): 111– 133.
[10] Kalakula, S., Malakulb, P., Siemanondb, K. and Gania, R. (2014). Integration of Life Cycle Assessment Software with Tools for Economic and Sustainability Analyses and Process Simulation for Sustainable Process Design. J. of Cleaner Production, Vol. 17, pp. 98-109.
[11] Haastrup, P., Maniezzo, V., Mattarelli, M., Rinaldi, F. M., Mendes, I. and Paruccini, M. (1989). A Decision Support System for Urban Waste Management. Eur. J. of Operational Research, 109(2): 330-341.
[12] Maniezzo, V., Mendes, I. and Paruccini, M. (1998). Decision Support for Siting Problems. J. of Decision Support Systems 23(3):273–284.
[13] Phillips, P. S., Read, A. D., Green, A. E. and Bates, M. P. (1999). UK Waste Minimisation Clubs: A Contribution to Sustainable Waste Management. J. of Resources, Conservation and Recycling 27(3): 217– 247.
[14] Kurian, J. (2006). Stakeholder Participation for Sustainable Waste Management. J. of Habitat Int., 30(4): 863–871.
[15] Shmeleva, S. E. and Powell, J.R. (2006). Ecological–economic Modelling for Strategic Regional Waste Management Systems. J. of Ecological Economics 59(1): 115-130.
[16] van de Klundert, A. and Anschutz, J. (1999). Integrated Sustainable Waste Management: the Selection of Appropriate Technologies and the Design of Sustainable Systems is Not (Only) a Technological issue. CEDARE/IETC Inter-regional Workshop on Technologies for Sustainable Waste Management, 1-17 Alexandria, Egypt.
[17] Wilson, E. J., McDougall, F. R. and Willmore, J. (2001). Euro-Trash: Searching Europe for a More Sustainable Approach to Waste management. J. of Resources Conservation and Recyclin,g 31(4), 327- 346.
[18] Bovea, M. D. and Powell, J. C. (2006). Alternative Scenarios to Meet the Demands of Sustainable Waste Management. J. of Environmental Management, vol. 79, pp. 115–132.
[19] den Boer. E. and Lager, J. (2007). LCA-IWM: A Decision Support Tool for Sustainability Assessment of Waste Management Systems. J. of Waste Management 27(8): 1032–1045.
[20] Thorneloe, S. A., Weitz, K., Barlaz, M. and Ham, R. K. (1999). Tools for Determining Sustainable Waste Management Through Application of Life-Cycle Assessment: Update on U.S. Research. in Proceedings of Seventh Int. Waste Management and Landfill Symp. V, pp. 629-636.
[21] McBean, E. A., del Rosso, E. and Rovers, F. A. (2005). Improvements in Financing for Sustainability in Solid Waste Management. J. of Resources, Conservation and Recycling 43(4): 391–401.
[22] Jadoon, A., Batool, S. A. and Chaudhry, M. N. (2014). Assessment of Factors Affecting Household Solid Waste Generation and its Composition in Gulberg Town, Lahore, Pakistan. J. of Mater Cycles Waste Management, 16(1):73–81, DOI 10.1007/s10163-013-0146-5.
[23] Worku Y. and Muchie, M. (2012). An Attempt at Quantifying Factors that Affect Efficiency in the Management of Solid Waste Produced by Commercial Businesses in the City of Tshwane, South Africa. J. of Environmental and Public Health, Hindawi Publishing Corporation, Vol. 2012, Article ID 165353, 12 p., doi:10.1155/2012/165353, Research Article.
[24] Beigl, P., Lebersorger and S., Salhofer (2008). Modelling Municipal Solid Waste Generation: A Review. J. of Waste Management, vol. 28, pp. 200–214.
[25] Langa, D. L., Binderb, C. R., Stauffachera, M., Zieglera, C., Schleiss, K., Scholz, R. W. (2006). Material and Money Flows as a Means for Industry Analysis of Recycling Schemes. A Case Study of Regional Bio- Waste Management. J of Resources, Conservation and Recycling, 49(06): 159-190.
[26] Morrissey, A. J. and Browne, J. (2004). Waste Management Models and Their Application to Sustainable Waste Management. J. of Waste Management 24(3): 297-308.
[27] M. K. Ketipi, D. E. Koulouriotis, E. G. Karakasis, G. A. Papakostas, V. D. Tourassis, A flexible nonlinear approach to represent cause–effect relationships in FCMs, Applied Soft Computing, Volume 12, Issue 12, December 2012, Pages 3757–3770.
[28] C. D. Stylios, P. P. Groumpos, Modelling Complex Systems Using Fuzzy Cognitive Maps, IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans, Vol. 34, No. 1, January 2004.
[29] K. Perusich, System Diagnosis Using Fuzzy Cognitive Maps, Cognitive Maps, Karl Perusich (Ed.), ISBN: 978-953-307-044-5, InTech, 2010.
[30] B. Kosko, Fuzzy Cognitive Maps, Int. J. Man-Machine Studies, 24, 65- 75, 1986.
[31] M. van Vliet, K. Kok, T. Veldkamp, Linking stakeholders and modellers in scenario studies: The use of Fuzzy Cognitive Maps as a communication and learning tool, Futures, Volume 42, Issue 1, February 2010, Pages 1–14.
[32] Papageorgiou, E. and Kontogianni, A. (2012). Using Fuzzy Cognitive Mapping in Environmental Decision Making and Management: A Methodological Primer and an Application. Int. Perspectives on Global Environmental Change, S. Young (ed.), ISBN: 978-953-307-815-1, InTech, doi: 10.5772/29375.
[33] Murungweni, C., M. T. Van Wijk, J. A. Andersson, E. M. A. Smaling, K. E. Giller, Application of fuzzy cognitive mapping in livelihood vulnerability analysis, Ecology and Society, 16(4): 8, 2011.
[34] K. G. Q. Isak, M. Wildenberg, M. Adamescu, F. Skov, G. De Blust, R. Varjopuro, A long-term biodiversity, Ecosystem and Awareness Research Network, Manual for applying Fuzzy Cognitive Mapping – experiences from ALTER-Net, Project No. GOCE-CT-2003-505298, 2009.