Optimizing Urban Resilience via FCM and Participatory Modeling: The Case of Joensuu Finland

Abstract

Improving community urban resilience necessitates a comprehensive awareness of all possible hazards and resilience choices, as well as the interests and objectives of many stakeholders, in order to create and implement inclusive and proactive interventions. For such complex urban ecosystems, we may utilize soft computing knowledge such as Fuzzy Theory and Decision Support Systems (DSS) to provide an innovative participatory model that identifies and quantifies urban resilience tradeoffs. We concentrate on the design of a Fuzzy Cognitive Map (FCM) that interlinks several participant perspectives in the form of semi-quantitative cause-and-effect linguistic responses from experts and stakeholders. More specifically, we analyze how this explainable Artificial Intelligence (XAI) cognitive model may assist decision-makers and competent authorities in developing urban resilience solutions. Based on stakeholders’ collective expertise the aggregated FCM determines the most advantageous initiatives in terms of their direct and indirect implications on urban resilience. We apply this model for the case of the city of Joensuu, Finland. For the use case, steady state analysis as well as best and worst-case scenarios are produced which are based on environmental, economic, social, and technological criteria. The prototype DSS is evaluated with both sigmoidal and hyperbolic tangent activations producing comparative results.