Mixed-method integration and advances in fuzzy cognitive maps for computational policy simulations for natural hazard mitigation

Environmental Modelling and Software

Volumn 39, Issue , 2013, Pages 188-200

  Samarasinghe, Sandhya ^a   Strickert, Graham ^b  

^a LINCOLN UNIVERSITY   (New Zealand)

^b UNIVERSITY OF SASKATCHEWAN   (Canada)

Author keywords

Auto Associative Neural Networks; Earthquakes; Fuzzy cognitive maps; Mixed method triangulation; Natural hazard mitigation; Policy simulation; Self organizing maps

Indexed keywords

ADAPTIVE CAPACITY; ADAPTIVE POLICY; AUTOASSOCIATIVE NEURAL NETWORKS; COMPUTATIONAL MODEL; DATA COLLECTION; EXPERT KNOWLEDGE; FUZZY COGNITIVE MAP; HUMAN SYSTEM; MAP STRUCTURE; MIXED METHOD; NATURAL HAZARD; NON-LINEAR RELATIONSHIPS; POLICY MAKERS; POLICY SCENARIO; POLICY SIMULATION; PUBLIC POLICY DECISIONS; QUALITATIVE INTERVIEWS; SELF-ORGANISING MAPS; SEMI-STRUCTURED; SOCIAL GROUPS; SOFT SCIENCE; STAKEHOLDER GROUPS; STAKEHOLDER PERCEPTION; SYSTEMS FRAMEWORK;

CONDENSATION; CONFORMAL MAPPING; DECISION MAKING; DYNAMICAL SYSTEMS; EARTHQUAKES; FUZZY RULES; GRAPH THEORY; HAZARDS; INTEGRATION; LARGE SCALE SYSTEMS; NEURAL NETWORKS; TRIANGULATION;

FUZZY SYSTEMS;

ADAPTIVE MANAGEMENT; ARTIFICIAL NEURAL NETWORK; COGNITION; DATA ACQUISITION; EARTHQUAKE; FUZZY MATHEMATICS; GRAPHICAL METHOD; HAZARD MANAGEMENT; NATURAL HAZARD; NUMERICAL MODEL; POLICY MAKING; STAKEHOLDER; TRIANGULATION;

EID: 84870301004     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2012.06.008     Document Type: Article

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