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Local Decision Making and Decision Fusion in Hierarchical Levels

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Date

2009

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Springer

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Abstract

Hierarchical problem solving is preferred when the problem is overwhelmingly complicated. In such a case, the problem should better be analyzed in hierarchical levels. At each level, some temporary solutions are obtained; then a suitable decision fusion technique is used to merge the temporary solutions for the next level. The hierarchical framework proposed in this study depends on reutilization or elimination of previous level local agents that together perform the decisions due to a decision-fusion technique: a performance criterion is set for local agents. The criterion checks the success of agents in their local regions. An agent satisfying this criterion is reutilized in the next level, whereas an agent not successful enough is removed from the agent pool in the next level. In place of a removed agent, a number of new local agents are developed. This framework is applied on a fault detection problem.

Description

Leblebicioglu, Mehmet Kemal/0000-0002-9735-458X

Keywords

Decision-Making, Decision-Fusion, Neural Networks, Classification, Machine Learning

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Citation

Beldek,Ulaş; Leblebicioglu, Kemal, "Local decision making and decision fusion in hierarchical levels",Top, Vol.17, No.1, pp.44-69, (2009).

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Q4

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Q2
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1

Source

International Workshop on Operational Research Conference held in honor of Laureano F Escudero -- JUN 05-07, 2008 -- Madrid, SPAIN

Volume

17

Issue

1

Start Page

44

End Page

69
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CrossRef : 1

Scopus : 5

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Mendeley Readers : 9

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