A decision making support tool: The resilience management fuzzy controller

In this paper a fuzzy controller capable to perform an automated estimation of the period of time necessary to recover a resilience level is proposed. Estimations where made by considering realistic time-dependent action changes for a set of resilience indicators originally proposed by Cardona (2001...

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Bibliographic Details
Published in2016 IEEE Congress on Evolutionary Computation (CEC) pp. 2313 - 2320
Main Authors Cardenas, J. Ruben G., Nebot, Angela, Mugica, Francisco, Vellido, Alfredo
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2016
Subjects
Artificial Intelligence
Decision Support System
Economic indicators
Estimation
Fuzzy Controllers
Fuzzy logic
Fuzzy sets
Inference System
Input variables
Machine Learning
Natural Hazards
Resilience
Resilience Management
Risk Management
Social Vulnerability
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Summary:In this paper a fuzzy controller capable to perform an automated estimation of the period of time necessary to recover a resilience level is proposed. Estimations where made by considering realistic time-dependent action changes for a set of resilience indicators originally proposed by Cardona (2001) and modified by Cardenas et al (2015). The fuzzy resilience controller works using two output control variables and four input variables designed to resemble politics decisions made over resilience recovery while considering an economical national growth factor. We applied the fuzzy controller onto Barcelona Spain, where different recovery times where estimated in terms of variations in Spaniard GDP (Gross domestic product) inter anual rate of change. This Decision Support System might be helpful to assist disaster reduction planning by allowing decision takers, governs or institutions to achieve reliable recovery time estimations while a proper supervision and control of resilience indicators progress is performed and an open evaluation and scrutiny of applied policies is made.
DOI:10.1109/CEC.2016.7744074