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http://hdl.handle.net/2307/40626
Cinwaan: | MODELLING RISK IN HIGHLY INTERDEPENDENT SYSTEMS | Qore: | PALAZZO, COSIMO | Tifaftire: | PANZIERI, STEFANO | Ereyga furaha: | RISK ANALYSIS DECISION SUPPORT SYSTEMS COMPLEX SYSTEMS MODELS |
Taariikhda qoraalka: | 18-Apr-2019 | Tifaftire: | Università degli studi Roma Tre | Abstract: | Understanding Risk represents the first step in the development of preparedness, re silience and mitigation strategies for governmental and non-governmental organisations. Building a common basis, in such a multidisciplinary context, becomes more and more a necessity because it helps us focus on the true nature of risk and not only on individual or circumstantial aspects which compose it. Starting from this perspective it is mandatory to continuously improve risk approaches and methodologies in our modern and fast changing society. The aim of this work is to provide a new Risk Analysis terminology-based framework and then introduce the MHR-RFB approach (Mixed Holistic Reductionist - Rational Fuzzy Bayesian) to model complex scenarios in highly interdependent systems. Subse quently an agent-based simulation software (CISIApro) is presented as a tool capable of implementing the MHR-RBF approach and promote a new Dynamic Risk Analysis (DRA). Thanks to the DRA it is possible to create a new generation of on-line tools able to dynamically assess the risk and supply an effective Decision Support System (DSS). In the second part of this work are proposed some applications of these strategies, in different critical contexts, to demonstrate how it is possible to convert risk data in a powerful source of information and use it to protect our contemporary society. | URI : | http://hdl.handle.net/2307/40626 | Xuquuqda Gelitaanka: | info:eu-repo/semantics/openAccess |
Wuxuu ka dhex muuqdaa ururinnada: | X_Dipartimento di Ingegneria T - Tesi di dottorato |
Fayl ku dhex jira qoraalkan:
Fayl | Sifayn | Baac | Fayl | |
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2019_Phd_Thesis_Cosimo_Palazzo.pdf | 9.79 MB | Adobe PDF | Muuji/fur |
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