Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

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Now showing 1 - 7 of 7
  • Book Part
    A Systematic Review of Optimization Studies Used in Renewable Energy Systems
    (Springer Science and Business Media Deutschland GmbH, 2026) Söylemez, İ.; Erdoğan, A.
    This study presents a literature review of recent studies on renewable energy systems. Due to the large number of studies, this study has been limited to some keywords. When only the word “renewable energy systems” is searched, there are more than 14,343 studies in the literature between 2017 and 2024. A systematic search was conducted for the studies in which “optimization” or “mathematical model” was mentioned as a solution methodology. A total of 755 studies were identified in the “Scopus database” and analyzed for these studies. A detailed examination was carried out for the type of studies (research article, review, conference paper, etc.), countries where the studies were carried out, authors who carried out the studies and their statistics with each other, and so on. With this study, an overview of the literature will be provided and it will be a guiding study for researchers on the direction of the studies. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
  • Article
    Citation - WoS: 24
    Citation - Scopus: 33
    Variable Structure Controllers for Unstable Processes
    (Elsevier Sci Ltd, 2015-08) Ablay, Gunyaz
    A variable structure control (VSC) method for unstable industrial processes is proposed. The proposed control method is able to provide a highly satisfactory system performance and to tackle with robustness issues of the processes in the presence of uncertainties. An ITAE-based numerical tuning algorithm for acquiring optimal control parameters, and a direct auto-tuning mechanism for the proposed controller are also provided. The performance of the proposed VSC method is illustrated on some unstable process models including a continuous stirred tank reactor (CSTR), in order to show its effectiveness, validity and feasibility. (C) 2015 Elsevier Ltd. All rights reserved.
  • Conference Object
    Citation - WoS: 8
    Citation - Scopus: 12
    SVM-RCE-R Optimization of Scoring Function for SVM-RCE
    (Springer International Publishing AG, 2021) Yousef, Malik; Jabeer, Amhar; Bakir-Gungor, Burcu
    Gene expression data classification provides a challenge in classification due to it having high dimensionality and a relatively small sample size. Different feature selection approaches have been used to overcome this issue and SVM-RCE being one of the more successful approach. This study is a continuation of two previous research studies SVM-RCE and SVM-RCE-R. SVM-RCE-R suggests a new approach in the scoring function for the clusters, showing that for some different combination of weights the performance was improved. The aim of this study is to find the optimal weights for the scoring function suggested in the study of SVM-RCE-R using optimization approaches. We have discovered that finding the optimal weights for the scoring function would improve the performance of the SVM-RCE-in most cases. We have shown that in some cases the performance is increased dramatically by 10% in terms of accuracy and AUC. By increasing the performance of the algorithm, it is more likely that we can extract subset genes relating to the class association of a microarray sample.
  • Article
    Citation - WoS: 24
    Citation - Scopus: 31
    On the Lifetime of Compressive Sensing Based Energy Harvesting in Underwater Sensor Networks
    (IEEE-Inst Electrical Electronics Engineers Inc, 2019-06-15) Erdem, Huseyin Emre; Yildiz, Huseyin Ugur; Gungor, Vehbi Cagri
    Recently, there has been a growing interest in academia and industry on the development of underwater acoustic sensor networks (UASNs) for scientific, commercial, and military purposes. Severe underwater channel conditions and limited battery energy of underwater nodes pose great challenges to prolong UASNs lifetime. Compressive sensing (CS), energy harvesting (EH), and transmission power control (TPC) are three promising solutions to improve UASNs lifetime. This paper aims to quantitatively investigate the joint impact of CS, EH, and TPC methods on the lifetime of UASNs. A novel Mixed Integer Programming framework is developed to maximize the network lifetime by joint consideration of CS, EH, and TPC. The performance results show that the impact of CS on the network lifetime is higher than that of EH when both methods are combined with TPC. Moreover, when all three methods are combined, the network lifetime can be extended up to three times as compared to the case when all three methods are not utilized.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 5
    Large Transformations With Moderate Strains of Tensile Membrane Structures
    (Sage Publications Ltd, 2016-04-28) Beatini, Valentina; Carfagni, Gianni Royer; Royer Carfagni, Gianni
    Using a classical non-linear theory, we analytically investigate possible ways for transforming the shape of a curved elastic membrane while keeping it tensioned and moderately strained. This is a critical issue because, as a rule, membranes must be considerably stretched in order to avoid wrinkling and slackening. If the final configuration is fixed, the membrane can be cut and formed according to the final shape, but this cannot be done if more configurations, considerably distant from one another, have to be achieved. Nevertheless, we propose large transformation movements that can be obtained starting from flat membranes while maintaining their strain as limited. We discuss in detail the paradigmatic example of the hyperbolic-paraboloid-shaped membrane. These opportunities are suitable for applications of transformable architecture because they do not require excessive tensioning, compatible with the strength of materials used for this kind of structures.
  • Book Part
    Hosting Capacity Calculation Methods
    (Elsevier, 2025) Oguzhan, Ceylan; Alper, Savasci
    In this chapter, we focus on hosting capacity (HC) calculations, by giving the methods to determine the maximum amount of distributed energy resources (DER) that can be integrated into power distribution network(s) without compromising reliability or performance. We detail methodologies such as power flow-based approaches, probabilistic techniques, and machine learning algorithms, with sample applications of HC calculations. Initially, we focus on power flow-based methods based on simulating power distribution network(s) to assess system voltage, current flow, and stability impacts from DER installations. Then, we will give the probabilistic approaches that use uncertainties in renewable generation and consumer demand, based on statistical techniques and Monte Carlo simulations aiming to reflect these variability. Machine learning (ML) techniques will also be given based on analyzing large data sets, detecting patterns, and predicting system responses. These kinds of methods include regression analysis and neural networks trained on historical data for optimized HC predictions. It should be stated that HC is impacted by several factors, such as network topology, load profiles, and DER characteristics, and these as well will be discussed. We will provide a practical example of an HC calculation on a 141-node distribution network using a step-by-step algorithm in Matpower, with simulation results based on an iterative deterministic method. Then, we will give the broader implications of HC assessments for grid modernization and energy policy, highlighting how accurate calculations support a more decentralized, sustainable, and resilient energy future. © 2025 Elsevier B.V., All rights reserved.
  • Conference Object
    Citation - Scopus: 5
    Enerji Hasadı ve Sıkıştırmalı Algılama Yapan Gizlilik Odaklı Sualtı Kablosuz Ağlarında Ömür Analizi
    (Institute of Electrical and Electronics Engineers Inc., 2019-04) Uyan, Osman Gokhan; Güngör, Vehbi Çağrı
    Underwater sensor networks (UWSN) are a division of classical wireless sensor networks (WSN), which are designed to accomplish both military and civil operations, such as invasion detection and underwater life monitoring. Underwater sensor nodes operate using the energy provided by integrated limited batteries, and it is a serious challenge to replace the battery under the water especially in harsh conditions with a high number of sensor nodes. Here, energy efficiency confronts as a very important issue. Besides energy efficiency, data privacy is another essential topic since UWSN typically generate delicate sensing data. UWSN can be vulnerable to silent positioning and listening, which is injecting similar adversary nodes into close locations to the network to sniff transmitted data. In this paper, we discuss the usage of compressive sensing (CS) and energy harvesting (EH) to improve the lifetime of the network whilst we suggest a novel encryption decision method to maintain privacy of UWSN. We also deploy a Mixed Integer Programming (MIP) model to optimize the encryption decision cases which leads to an improved network lifetime. © 2020 Elsevier B.V., All rights reserved.