Data stream management systems exist to support dynamic analysis of streaming data, often to inform decision-making. Decision Support Systems (DSSs) exist to enable decisions to be made that take into account user priorities. However, although these categories of system are now quite mature, there has been little work investigating their use together. Bringing these technologies together in a way that enables trustable decision support for dynamic applications is a difficult problem with particular impact in the military and medical domains. A framework has been proposed, comprising eight desiderata for trusted dynamic decision support. These desiderata aim to inform architects of dynamic DSSs on the implications of different capacities for decision support. An approach to dynamic decision support employing Genetic Algorithms (GAs) has been proposed. Two case studies have been utilised to show how this approach can be leveraged to provision DSSs with our desiderata. Weighted Product Model (WPM), Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) have been assessed on the stability of results and the consistency of trade-offs, two of our desiderata. This assessment determined TOPSIS to be the method that is the most suitable for dynamic decision support. The problem of evaluating the effect of DSS features on trust has also been addressed and a theoretical framework modelling trust and its antecedents in a real-time DSS has been proposed. This model has then been used to carry out an assessment of the impact of explanation, preferences and dynamic updates as components of dynamic decision support, giving designers of DSSs an indication of which of these features are likely to have a positive impact on decision making in a dynamic environment. Finally, the research has concluded with the identification and discussion of potential areas for future investigation.
Date of Award | 1 Aug 2022 |
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Original language | English |
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Awarding Institution | - The University of Manchester
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Supervisor | John Keane (Supervisor) & Norman Paton (Supervisor) |
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- Genetic Algorithms
- Decision Support Systems
- Stream Processing
Trustable Decision Support for Dynamic Applications
Duxbury, D. (Author). 1 Aug 2022
Student thesis: Phd