Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Hakan Ezgi Kiziloz"'
Autor:
Ayca Deniz, Hakan Ezgi Kiziloz
Publikováno v:
2022 International Joint Conference on Neural Networks (IJCNN).
Autor:
Hakan Ezgi Kiziloz
Publikováno v:
Neurocomputing. 419:97-107
Feature selection has become an indispensable preprocessing step in an expert system. Improving the feature selection performance could guide such a system to make better decisions. Classifier ensembles are known to improve performance when compared
Publikováno v:
Pattern Recognition Letters, 140, 245-251. Elsevier
Predicting the gender of a text document’s author, also known as gender identification, is a well-studied authorship categorization task in the literature. A common theme in gender identification studies is that gender is considered a binary task.
Autor:
Hakan Ezgi Kiziloz
Publikováno v:
Volume: 8, Issue: 1 57-61
Balkan Journal of Electrical and Computer Engineering
Balkan Journal of Electrical and Computer Engineering
Wireless sensor networks (WSN) has been a prominent topic for the past decade. WSN consist of multiple sensor nodes, which collect and convey data to the base station(s). Sensor nodes are expected to run on batteries, and it makes energy the scarce r
Publikováno v:
Expert Systems. 39
The COVID-19 pandemic has huge effects on the global community and an extreme burden on health systems. There are more than 185 million confirmed cases and 4 million deaths as of July 2021. Besides, the exponential rise in COVID-19 cases requires a q
Autor:
Ayça Deniz, Hakan Ezgi Kiziloz
Publikováno v:
Expert Systems with Applications. 137:11-21
Performance of evolutionary algorithms depends on many factors such as population size, number of generations, crossover or mutation probability, etc. Generating the initial population is one of the important steps in evolutionary algorithms. A poor
Autor:
Ayça Deniz, Hakan Ezgi Kiziloz
Publikováno v:
SMC
With the advance in technology, the volume of available data grows massively. Therefore, feature selection has become an essential preprocessing step to extract valuable information. Feature selection is the task of reducing the number of features by
Publikováno v:
Neurocomputing. 306:94-107
Teaching Learning Based Optimization (TLBO) is a new metaheuristic that has been successfully applied to several intractable optimization problems in recent years. In this study, we propose a set of novel multiobjective TLBO algorithms combined with
A robust and cooperative parallel tabu search algorithm for the maximum vertex weight clique problem
Autor:
Hakan Ezgi Kiziloz, Tansel Dokeroglu
Publikováno v:
Computers & Industrial Engineering. 118:54-66
The maximum vertex weight clique problem (MVWCP) is a challenging NP-Hard combinatorial optimization problem that searches for a clique with maximum total sum of vertices’ weights. In this study, we propose a robust and cooperative parallel tabu se
Publikováno v:
Knowledge-Based Systems. 227:107219
The Harris’ Hawks Optimization (HHO) is a recent metaheuristic inspired by the cooperative behavior of the hawks. These avians apply many intelligent techniques like surprise pounce (seven kills) while they are catching their prey according to the