Bilgisayar Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1940

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Browsing Bilgisayar Mühendisliği Bölümü Koleksiyonu by Institution Author "Bekmezci, İlker"

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    Article
    Citation - WoS: 1
    Citation - Scopus: 2
    A Novel Genetic Algorithm-Based Improvement Model for Online Communities and Trust Networks
    (IOS Press, 2020) Bekmezci, ilker; Cimen, Egemen Berkic; Ermiş, Murat
    Social network analysis offers an understanding of our modern world, and it affords the ability to represent, analyze and even simulate complex structures. While an unweighted model can be used for online communities, trust or friendship networks should be analyzed with weighted models. To analyze social networks, it is essential to produce realistic social models. However, there are serious differences between social network models and real-life data in terms of their fundamental statistical parameters. In this paper, a genetic algorithm (GA)-based social network improvement method is proposed to produce social networks more similar to real-life data sets. First, it creates a social model based on existing studies in the literature, and then it improves the model with the proposed GA-based approach based on the similarity of the average degree, the k-nearest neighbor, the clustering coefficient, degree distribution and link overlap. This study can be used to model the structural and statistical properties of large-scale societies more realistically. The performance results show that our approach can reduce the dissimilarity between the created social networks and the real-life data sets in terms of their primary statistical properties. It has been shown that the proposed GA-based approach can be used effectively not only in unweighted networks but also in weighted networks.
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    Conference Object
    Citation - WoS: 6
    Citation - Scopus: 6
    Efficient Strategy for Multi-Uav Path Planning in Target Coverage Problems
    (IEEE, 2022) Bekmezci, İlker; Pehlivanoğlu, Perihan; Pehlivanoğlu, Y. Volkan
    In recent years, multi unmanned aerial vehicles (UAVs) are used in the same system to accomplish more complex missions. In many multi-UAV system applications, the main objective is to visit some predetermined checkpoints in operational area. If the number of check points and constraints increases, finding a feasible solution takes up too much time. In this paper, a checkpoint based multi-UAV path planning problem is solved by using improved genetic algorithm. The main contributions of this paper are: (1) the introducing revisit time interval concept, (2) the investigating of the effect of objective function description, and (3) looking into an outcome of using multiple runways on optimal multi-UAV path planning. The proposed strategy-based optimization methodology is performed for checkpoint based multi-UAV path planning problems in two-dimensional (2D) environment. Performance results show that the proposed strategy provides effective and feasible paths for each UAV.