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Utilization and Comparison of Multi Attribute Decision Making Techniques to Rank Bayesian Network Options
University of Skövde, School of Humanities and Informatics.
2011 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

A fusion system sometimes requires the capability to represent the temporal changes of uncertain sensory information in dynamic and uncertain situation. A Bayesian Network can construct a coherent fusion structure with the hypothesis node which cannot be observed directly and sensors through a number of intermediate nodes that are interrelated by cause and effect. In some BN applications for observing a hypothesis node with the number of participated sensors, rank and select the appropriate options (different combination of sensors allocation) in the decision-making is a challenging problem. By user interaction, we can acquire more and useful information through multi-criteria decision aid (MCDA) as semi-automatically decision support. So in this study, Multi Attribute Decision Making (MADM) techniques as TOPSIS, SAW, and Mixed (Rank Average) for decision-making as well as AHP and Entropy for obtaining the weights of indexes have been used. Since MADM techniques have most probably different results according to different approaches and assumptions in the same problem, statistical analysis done on them. According to results, the correlation between applied techniques for ranking BN options is strong and positive because of the close proximity of weights suggested by AHP and Entropy. Mixed method as compared to TOPSIS and SAW is ideal techniques; moreover, AHP is more acceptable than Entropy for weighting of indexes.

Place, publisher, year, edition, pages
2011. , 58 p.
Keyword [en]
Multi Attribute Decision Making (MADM), Bayesian Networks, Sensor Allocation, AHP, Entropy, TOPSIS, SAW
National Category
Information Science Information Science
Identifiers
URN: urn:nbn:se:his:diva-5276OAI: oai:DiVA.org:his-5276DiVA: diva2:438047
Subject / course
Computer Science
Educational program
Informatics - Master's Programme
Presentation
2011-06-01, University of Skövde, P.O. Box 408, SE-541 28 Skövde, SWEDEN, Skövde, 14:00 (English)
Uppsok
Technology
Supervisors
Examiners
Available from: 2011-09-01 Created: 2011-08-31 Last updated: 2011-09-09Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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More styles
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  • de-DE
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  • en-US
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  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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