Ahmet Coşar

E-mail

cosar@metu.edu.tr

Department

Department of Computer Engineering

ORCID

0000-0002-3090-2254

Web of Science Researcher ID

C-7700-2012

An island-parallel ensemble metaheuristic algorithm for large graph coloring problems Coşar, Ahmet (2025-04-01) Graph Coloring Problem (GCP) is an NP-Hard vertex labeling problem in graphs such that no two adjacent vertices can have the same color. Large instances of GCP cannot be solved in reasonable execution times by exact al...
Abstract or Full-text in Topic Modeling? Konu Modellemede Özet mi Tam Metin mi? Tekin, Yasar; Coşar, Ahmet (2022-01-01) Topic modeling is a text mining technique used for automatic extraction of topics addressed in document collections. Although there are different topic models proposed by researchers, the most preferred one is Latent Diric...
A new framework of multi-objective evolutionary algorithms for feature selection and multi-label classification of video data Karagoz, Gizem Nur; Yazıcı, Adnan; Dokeroglu, Tansel; Coşar, Ahmet (2020-06-01) There are few studies in the literature to address the multi-objective multi-label feature selection for the classification of video data using evolutionary algorithms. Selecting the most appropriate subset of features is ...
Application of binary PSO for public cloud resources allocation system of video on demand (VoD) services Aygun, Betul; Günel Kılıç, Banu; ARICI, NURSAL; Coşar, Ahmet; Tuncsiper, Bedriye (Elsevier BV, 2020-01-01) Video streaming, whether on demand or live, has become one of the most popular internet applications. However, financial investments required for it is a severe problem since it needs more real time storage, higher data tr...
A survey on new generation metaheuristic algorithms Dökeroğlu, Tansel; Sevinc, Ender; Dökeroğlu, Tansel; Coşar, Ahmet (2019-11-01) Metaheuristics are an impressive area of research with extremely important improvements in the solution of intractable optimization problems. Major advances have been made since the first metaheuristic was proposed and num...
Context-sensitive and keyword density-based supervised machine learning techniques for malicious webpage detection Altay, Betul; Dokeroglu, Tansel; Coşar, Ahmet (2019-06-01) Conventional malicious webpage detection methods use blacklists in order to decide whether a webpage is malicious or not. The blacklists are generally maintained by third-party organizations. However, keeping a list of all...
Visual and Auditory Data Fusion for Energy-Efficient and Improved Object Recognition in Wireless Multimedia Sensor Networks Koyuncu, Murat; Yazici, Adnan; Civelek, Muhsin; Coşar, Ahmet; Sert, Mustafa (2019-03-01) Automatic threat classification without human intervention is a popular research topic in wireless multimedia sensor networks (WMSNs) especially within the context of surveillance applications. This paper explores the effe...
An expandable approach for design and personalization of digital, just-in-time adaptive interventions Gonul, Suat; Namli, Tuncay; Huisman, Sasja; Erturkmen, Gokce Banu Laleci; Toroslu, İsmail Hakkı; Coşar, Ahmet (2019-03-01) Objective: We aim to deliver a framework with 2 main objectives: 1) facilitating the design of theory-driven, adaptive, digital interventions addressing chronic illnesses or health problems and 2) producing personalized in...
Artificial bee colony optimization for the quadratic assignment problem Dökeroğlu, Tansel; Sevinc, Ender; Coşar, Ahmet (2019-03-01) We propose hybrid Artificial Bee Colony (ABC) optimization algorithms for the well-known Quadratic Assignment Problem (QAP). Large problem instances of the QAP are still very challenging. Scientists have not discovered any...
Novel multiobjective TLBO algorithms for the feature subset selection problem Kiziloz, Hakan Ezgi; Deniz, Ayca; Dokeroglu, Tansel; Coşar, Ahmet (2018-09-06) 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 TL...

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