In multi-level decision making (DM) approaches, the final decision is reached by
going through a finite number of DM levels. Usually, in each level, a raw decision
is produced first and then a suitable decision fusion technique is employed to
merge the lower level decisions with the raw decision in the construction of the
final decision of the present level. The basic difficulty in these approaches is the
determination of how the consecutive levels should interact with each other. In this
thesis, two different multi-level DM models have been proposed. The main idea in
the first model, &ldquo / hierarchical DM&rdquo / (HDM), is to transfer the decisions of previous
hierarchical levels to an upper hierarchy with some reliability values. These
decisions are then fused using a suitable decision fusion technique to attain more
consistent decisions at an upper level. The second model &ldquo / local DM in multiplelevels&rdquo / (LDM-ML) depends on what may be called as local DM process. Instead
of designing an agent to perform globally, designing relatively simple agents
which are supposed to work in local regions is the essence of the second idea.
Final decision is partially constructed by contribution of a sufficient number of
local DM agents. A successful local agent is retained in the agent pool whereas a
local agent not successful enough is eliminated and removed from the agent pool.
These models have been applied on two case studies associated with fault
detection in a four-tank system and prediction of lotto sales.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12610702/index.pdf |
| Date | 01 June 2009 |
| Creators | Beldek, Ulas |
| Contributors | Leblebicioglu, Kemal |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | Ph.D. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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