Beldek, Ulaş

Beldek, Ulaş

Profile URL

https://hdl.handle.net/20.500.12416/8882

Name Variants

Beldek, U.
Beldek, Ulas

Job Title

Dr. Öğr. Üyesi

Email Address

u.beldek@cankaya.edu.tr

Main Affiliation

Mekatronik Mühendisliği

Status

Current Staff

ORCID ID

0000-0003-1143-1829

Files

00508.jpeg (21.91 KB)

Full item page

Sustainable Development Goals

13

CLIMATE ACTION

0

Research Products

8

DECENT WORK AND ECONOMIC GROWTH

0

Research Products

3

GOOD HEALTH AND WELL-BEING

0

Research Products

15

LIFE ON LAND

0

Research Products

17

PARTNERSHIPS FOR THE GOALS

0

Research Products

14

LIFE BELOW WATER

0

Research Products

4

QUALITY EDUCATION

0

Research Products

11

SUSTAINABLE CITIES AND COMMUNITIES

0

Research Products

6

CLEAN WATER AND SANITATION

0

Research Products

10

REDUCED INEQUALITIES

0

Research Products

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE

0

Research Products

12

RESPONSIBLE CONSUMPTION AND PRODUCTION

0

Research Products

2

ZERO HUNGER

0

Research Products

1

NO POVERTY

0

Research Products

7

AFFORDABLE AND CLEAN ENERGY

2

Research Products

5

GENDER EQUALITY

0

Research Products

16

PEACE, JUSTICE AND STRONG INSTITUTIONS

2

Research Products

This researcher does not have a Scopus ID.

This researcher does not have a WoS ID.

Scholarly Output

16

Articles

8

Views / Downloads

2810/913

Supervised MSc Theses

1

Supervised PhD Theses

0

WoS Citation Count

27

Scopus Citation Count

35

WoS h-index

3

Scopus h-index

4

Patents

0

Projects

0

WoS Citations per Publication

1.69

Scopus Citations per Publication

2.19

Open Access Source

5

Supervised Theses

1

Google Analytics Visitor Traffic

Journal	Count
Information Sciences	2
IFAC Proceedings Volumes (IFAC-PapersOnline)	2
22nd International Symposium on Computer and Information Sciences -- NOV 07-09, 2007 -- Ankara, TURKEY	1
Applied Optics	1
Çankaya University Journal of Science and Engineering	1

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Scholarly Output Search Results

Now showing 1 - 10 of 16

Citation - WoS: 2
Citation - Scopus: 4
A New Systematic and Flexible Method for Developing Hierarchical Decision-Making Models
(Tubitak Scientific & Technological Research Council Turkey, 2015) Beldek, Ulas; Leblebicioglu, Mehmet Kemal
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 levels increase, the information associated with these agents is combined through suitable processes and agents with higher complexity are formed to carry out the DM tasks more elegantly. The HDM model is applied to the case study 'Fault degree classification in a 4-tank water circulation system'. For this case study, the processes that connect the lower levels to the higher levels are agent development processes where a special decision fusion technique is its integral part. This decision fusion technique combines the previous level's decisions and their performance indicator suitably to contribute to the improvement of new agents in higher levels. Additionally, the proposed agent development process provides flexibility both in the training and validation phases, and less computational effort is required in the training phase compared to a single-agent development simulation carried out for the same DM task under similar circumstances. Hence, the HDM model puts forward an enhanced performance compared to a single agent with a more sophisticated structure. Finally, model validation and efficiency in the presence of noise are also simulated. The adaptability of the agent development process due to the flexible structure of the model also accounts for improved performance, as seen in the results.
Model Based PI Controller Design and Test of a DC Motor Using Root Locus
(2019) Beldek, Ulaş; Mahmood, Ahmed Imad
:In this paper the mathematical model of an experimental DC motor control system is constructed in a simulative environment for speed (angular velocity) control process and a PI controller is designed using root locus technique. The designed controller is then tested in different scenarios with varying reference signalsand changing disturbance load conditions. The designed controller demonstrated satisfactory results in simulations.
Citation - WoS: 5
Citation - Scopus: 9
Strategy Creation, Decomposition and Distribution in Particle Navigation
(Elsevier Science inc, 2007) Leblebicioglu, Kemal; Beldek, Ulas
Strategy planning is crucial to control a group to achieve a number of tasks in a closed area full of obstacles. In this study, genetic programming has been used to evolve rule-based hierarchical structures to move the particles in a grid region to accomplish navigation tasks. Communications operations such as receiving and sending commands between particles are also provided to develop improved strategies. In order to produce more capable strategies, a task decomposition procedure is proposed. In addition, a conflict module is constructed to handle the challenging situations and conflicts such as blockage of a particle's pathway to destination by other particles. (C) 2006 Elsevier Inc. All rights reserved.
Citation - WoS: 3
Citation - Scopus: 5
Local Decision Making and Decision Fusion in Hierarchical Levels
(Springer, 2009) Leblebicioglu, Kemal; Beldek, Ulas
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.
Developing growing hierarchical structures for decision making
(IEEE, 2007) Beldek, Ulaş; Leblebicioğlu, Kemal
This study is about developing a hierarchical approach for decision-making problems. The development is done on a representative decision-making problem. A hierarchical decision making approach which enables fusion of decisions of previous and current levels is proposed. The agents that determine the decisions at different hierarchy levels is accomplished by utilizing a genetic algorithm.
Developing Growing Hierarchical Structures for Decision Making
(Ieee, 2007) Beldek, U.; Leblebicioglu, K.
This study is about developing a hierarchical approach for decision-making problems. The development is done on a representative decision-making problem. A hierarchical decision making approach which enables fusion of decisions of previous and current levels is proposed. The agents that determine the decisions at different hierarchy levels is accomplished by utilizing a genetic algorithm.
Hierarchical decision making and decision fusion
(IEEE, 2007) Beldek, Ulaş; Leblebicioğlu, Kemal
In this study, a hierarchical decision making structure possessing a decision fusion technique is proposed in order to solve decision making problems efficiently. The proposed structure mainly depends on effects of the decisions made in the lower levels to decisions in the upper levels up to an activation degree. The proposed hierarchical structure is used for detecting the fault degrees for single and multiple fault scenarios artifically generated in a four tank system. The results obtained demonstrate the effectiveness of the proposed hierarchical decision making structure.
Citation - Scopus: 1
Local Decision-Making in Multiple Levels for Lottery Data Analysis
(IFAC Secretariat, 2011) Leblebicioǧlu, K.; Beldek, U.
Sales forecasting is a common problem in economics. Lottery sales are one of the favorite issues of sales forecasting. Sales of lottery tickets depend on many economical issues and such a problem was investigated previously (Beensock et al., 2002) where Genetic Programming is used in order to construct different agent structures that predict the number of ticket sales in Israel lottery. In each application in (Beensock et al., 2002), only a single agent is developed to predict the number of ticket sales at a present drawing. Instead we propose a Local Decision-Making model which performs the sales forecasting job in multiple levels by employing agent structures that operate locally and combine their decisions via a suitable decision fusion technique. It seems that Local Decision-Making in Multiple Levels fits well for the problem. © 2011 IFAC.
Citation - WoS: 17
Citation - Scopus: 16
Developing and Implementation of an Optimization Technique for Solar Chimney Power Plant With Machine Learning
(Asme, 2021) Kocak, Eyup; Bayer, Ozgur; Beldek, Ulas; Yapic, Ekin Ozgirgin; Ayli, Ece; Ulucak, Oguzhan
Green energy has seen a huge surge of interest recently due to various environmental and financial reasons. To extract the most out of a renewable system and to go greener, new approaches are evolving. In this paper, the capability of Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System in geometrical optimization of a solar chimney power plant (SCPP) to enhance generated power is investigated to reduce the time cost and errors when optimization is performed with numerical or experimental methods. It is seen that both properly constructed artificial neural networks (ANN) and adaptive-network-based fuzzy inference system (ANFIS) optimized geometries give higher performance than the numerical results. Also, to validate the accuracy of the ANN and ANFIS predictions, the obtained results are compared with the numerical results. Both soft computing methods over predict the power output values with MRE values of 12.36% and 7.25% for ANN and ANFIS, respectively. It is seen that by utilizing ANN and ANFIS algorithms, more power can be extracted from the SCPP system compared to conventional computational fluid dynamics (CFD) optimized geometry with trying a lot more geometries in a notably less time when it is compared with the numerical technique. It is worth mentioning that the optimization method that is developed can be implemented to all engineering problems that need geometric optimization to maximize or minimize the objective function.
Strategy creation, decomposition and distribution in particle navigation
(Elsevier Science, 2007) Beldek, Ulaş; Leblebicioğlu, Kemal
Strategy planning is crucial to control a group to achieve a number of tasks in a closed area full of obstacles. In this study, genetic programming has been used to evolve rule-based hierarchical structures to move the particles in a grid region to accomplish navigation tasks. Communications operations such as receiving and sending commands between particles are also provided to develop improved strategies. In order to produce more capable strategies, a task decomposition procedure is proposed. In addition, a conflict module is constructed to handle the challenging situations and conflicts such as blockage of a particle's pathway to destination by other particles

Beldek, Ulaş

Profile URL

Name Variants

Job Title

Email Address

Main Affiliation

Status

Website

ORCID ID

Scopus Author ID

Turkish CoHE Profile ID

Google Scholar ID

WoS Researcher ID

Files

Sustainable Development Goals

13

CLIMATE ACTION

0

Research Products

8

DECENT WORK AND ECONOMIC GROWTH

0

Research Products

3

GOOD HEALTH AND WELL-BEING

0

Research Products

15

LIFE ON LAND

0

Research Products

17

PARTNERSHIPS FOR THE GOALS

0

Research Products

14

LIFE BELOW WATER

0

Research Products

4

QUALITY EDUCATION

0

Research Products

11

SUSTAINABLE CITIES AND COMMUNITIES

0

Research Products

6

CLEAN WATER AND SANITATION

0

Research Products

10

REDUCED INEQUALITIES

0

Research Products

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE

0

Research Products

12

RESPONSIBLE CONSUMPTION AND PRODUCTION

0

Research Products

2

ZERO HUNGER

0

Research Products

1

NO POVERTY

0

Research Products

7

AFFORDABLE AND CLEAN ENERGY

2

Research Products

5

GENDER EQUALITY

0

Research Products

16