Modelling Socio-ecological Systems: Implementation of an Advanced Fuzzy Cognitive Map Framework for Policy development for addressing complex real-life challenges
Mamoon Obiedat, Sandhya Samarasinghe

TL;DR
This paper introduces an advanced fuzzy cognitive map framework for modeling complex socio-ecological systems, demonstrated through a case study on water scarcity in Jordan, integrating stakeholder perceptions and neural network simulations.
Contribution
It presents a novel fuzzy 2-tuple framework for large FCM analysis, including condensation, aggregation, and neural network simulation for policy development.
Findings
Successfully modeled a complex water scarcity system with 186 variables.
Generated and analyzed multiple stakeholder FCMs and a comprehensive system map.
Identified high-impact policy strategies using fuzzy AANN simulations.
Abstract
This study implements a novel Fuzzy Cognitive Map (FCM) framework for addressing large complex socio-ecological problems. These are characterized as qualitative, dominated by uncertainty, human involvement with different and vague perceptions/expectations, and complex systems dynamics due to feedback relations. The FCM framework provides a participatory soft computing approach to develop consensus solutions. We demonstrate its implementation in a case study: a national-scale acute water scarcity crisis. The model has eight steps starting from collecting data from stakeholders in the form of FCMs (bi-directional graphs) represented by nodes and imprecise connections. All subsequent steps operate within a new fuzzy 2-tuple framework that overcomes previous FCM limitations through advanced processing methods, where large FCMs are fuzzified and analyzed, condensed, and aggregated using…
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Taxonomy
TopicsCognitive Science and Mapping
