An ontology-oriented decision support system for emergency management based on information fusion

2015 ◽  
Author(s):  
Yaoci Han ◽  
Wei Xu
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Emergency Management ◽  
Information Fusion ◽  
Support System

A Distributed Scenario-Based Decision Support System for Robust Decision-Making in Complex Situations

2013 ◽  
pp. 213-231
Author(s):  
Tina Comes ◽  
Niek Wijngaards ◽  
Michael Hiete ◽  
Claudine Conrado ◽  
Frank Schultmann
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Emergency Management ◽  
Distributed System ◽  
Support System ◽  
Irrelevant Information ◽  
Informed Decision Making ◽  
Processing Information ◽  
Flexible Adaptation

Decision-making in emergency management is a challenging task as the consequences of decisions are considerable, the threatened systems are complex and information is often uncertain. This paper presents a distributed system facilitating better-informed decision-making in strategic emergency management. The construction of scenarios provides a rationale for collecting, organising, and processing information. The set of scenarios captures the uncertainty of the situation and its developments. The relevance of scenarios is ensured by gearing the scenario construction to assessing alternatives, thus avoiding time-consuming processing of irrelevant information. The scenarios are constructed in a distributed setting allowing for a flexible adaptation of reasoning (principles and processes) to both the problem at hand and the information available. This approach ensures that each decision can be founded on a coherent set of scenarios. The theoretical framework is demonstrated in a distributed decision support system by orchestrating experts into workflows tailored to each specific decision.

scholarly journals A Review of Information Fusion Methods for Gas Turbine Diagnostics

2019 ◽  
Vol 11 (22) ◽  
pp. 6202 ◽  
Author(s):  
Valentina Zaccaria ◽  
Moksadur Rahman ◽  
Ioanna Aslanidou ◽  
Konstantinos Kyprianidis
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Gas Turbine ◽  
Information Fusion ◽  
Support System ◽  
Probabilistic Reasoning ◽  
Decision Fusion ◽  
Lessons Learned ◽  
Diagnostic Systems ◽  
Fusion Methods

The correct and early detection of incipient faults or severe degradation phenomena in gas turbine systems is essential for safe and cost-effective operations. A multitude of monitoring and diagnostic systems were developed and tested in the last few decades. The current computational capability of modern digital systems was exploited for both accurate physics-based methods and artificial intelligence or machine learning methods. However, progress is rather limited and none of the methods explored so far seem to be superior to others. One solution to enhance diagnostic systems exploiting the advantages of various techniques is to fuse the information coming from different tools, for example, through statistical methods. Information fusion techniques such as Bayesian networks, fuzzy logic, or probabilistic neural networks can be used to implement a decision support system. This paper presents a comprehensive review of information and decision fusion methods applied to gas turbine diagnostics and the use of probabilistic reasoning to enhance diagnostic accuracy. The different solutions presented in the literature are compared, and major challenges for practical implementation on an industrial gas turbine are discussed. Detecting and isolating faults in a system is a complex problem with many uncertainties, including the integrity of available information. The capability of different information fusion techniques to deal with uncertainty are also compared and discussed. Based on the lessons learned, new perspectives for diagnostics and a decision support system are proposed.

A Distributed Scenario-Based Decision Support System for Robust Decision-Making in Complex Situations

2011 ◽  
Vol 3 (4) ◽  
pp. 17-35 ◽  
Author(s):  
Tina Comes ◽  
Niek Wijngaards ◽  
Michael Hiete ◽  
Claudine Conrado ◽  
Frank Schultmann
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Emergency Management ◽  
Support System ◽  
Irrelevant Information ◽  
Informed Decision Making ◽  
Processing Information ◽  
Flexible Adaptation ◽  
Distributed Decision

Decision-making in emergency management is a challenging task as the consequences of decisions are considerable, the threatened systems are complex and information is often uncertain. This paper presents a distributed system facilitating better-informed decision-making in strategic emergency management. The construction of scenarios provides a rationale for collecting, organising, and processing information. The set of scenarios captures the uncertainty of the situation and its developments. The relevance of scenarios is ensured by gearing the scenario construction to assessing alternatives, thus avoiding time-consuming processing of irrelevant information. The scenarios are constructed in a distributed setting allowing for a flexible adaptation of reasoning (principles and processes) to both the problem at hand and the information available. This approach ensures that each decision can be founded on a coherent set of scenarios. The theoretical framework is demonstrated in a distributed decision support system by orchestrating experts into workflows tailored to each specific decision.

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