Design and improvement of multi-level decision-making models

Download

index.pdf

Date

2009

Author

Beldek, Ulaş

Metadata

Show full item record

Item Usage Stats

150
views

55
downloads

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, “hierarchical DM” (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 “local DM in multiplelevels” (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.

Subject Keywords

Electrical engineering.

URI

http://etd.lib.metu.edu.tr/upload/12610702/index.pdf
https://hdl.handle.net/11511/18758

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

A new systematic and flexible method for developing hierarchical decision-making models BELDEK, ULAŞ; Leblebicioğlu, Mehmet Kemal (2015-01-01) The common practice in multilevel decision-making (DM) systems is to achieve the final decision by going through a finite number of DM levels. In this study, a new multilevel DM model is proposed. This model is called the hierarchical DM (HDM) model and it is supposed to provide a flexible way of interaction and information flow between the consecutive levels that allows policy changes in DM procedures if necessary. In the model, in the early levels, there are primary agents that perform DM tasks. As the le...
Efficient solution of optimization problems with constraints and/or cost functions expensive to evaluate Kurtdere, Ahmet Gökhan; Leblebicioğlu, Mehmet Kemal; Department of Electrical and Electronics Engineering (2009) There are many optimization problems motivated by engineering applications, whose constraints and/or cost functions are computationally expensive to evaluate. What is more derivative information is usually not available or available at a considerable cost. For that reason, classical optimization methods, based on derivatives, are not applicable. This study presents a framework based on available methods in literature to overcome this important problem. First, a penalized model is constructed where the viola...
Control law partitioning applied to beam and ball system Koçak, Elif; Kocaoğlan, Erol; Department of Electrical and Electronics Engineering (2008) In this thesis different control methods are applied to the beam and ball system. Test setup for the previous thesis is handled, circuit assemblies and hardware redesigned. As the system is controlled by the control law partitioning method by a computer, discrete time system model is created. The controllability and the observability of the system are analyzed and a nonlinear controller by using control law partitioning in other words computed torque is designed. State feedback control algorithm previously ...
A comparative evaluation of conventional and particle filter based radar target tracking Yıldırım, Berkin; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2007) In this thesis the radar target tracking problem in Bayesian estimation framework is studied. Traditionally, linear or linearized models, where the uncertainty in the system and measurement models is typically represented by Gaussian densities, are used in this area. Therefore, classical sub-optimal Bayesian methods based on linearized Kalman filters can be used. The sequential Monte Carlo methods, i.e. particle filters, make it possible to utilize the inherent non-linear state relations and non-Gaussian no...
Robust set-valued estimation and its application to in-flight alignment of sins Seymen, Niyazi Burak; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2005) In this thesis, robust set-valued estimation is studied and its application to in-flight alignment of strapdown inertial navigation systems (SINS) with large heading uncertainty is performed. It is known that the performance of the Kalman filter is vulnerable to modeling errors. One of the estimation methods, which are robust against modeling errors, is robust set-valued estimation. In this approach, the filter calculates the set of all possible states, which are consistent with uncertainty inputs satisfyin...

Citation Formats

U. Beldek, “Design and improvement of multi-level decision-making models,” Ph.D. - Doctoral Program, Middle East Technical University, 2009.