Yazar "Aydemir, Salih Berkan" için listeleme
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Application of a metaheuristic gradient-based optimizer algorithm integrated into artificial neural network model in a local geoid modeling with global navigation satellite systems/leveling measurements
Konakoglu, Berkant; Aydemir, Salih Berkan; Onay, Funda Kutlu (Wiley, 2022)In the present article, the efficiency of a new hybrid learning method, named artificial neural network with gradient-based optimizer algorithm (ANN-GBO), is investigated to determine a local geoid. The outcomes of the ... -
Chaotic hunger games search optimization algorithm for global optimization and engineering problems
Onay, Funda Kutlu; Aydemir, Salih Berkan (Elsevier, 2022)Chaotic maps have the characteristics of ergodicity and non-repeatability. Owing to these properties, they provide fast convergence by effectively scanning the search space in a metaheuristic optimization algorithm. The ... -
Comparative Analysis of Globalisation Techniques for Medical Document Classification
Parlak, Bekir; Aydemir, Salih Berkan (Mahmut DİRİK, 2023)Medical document classification is one of the important topics of text mining. Globalisation techniques play a major role in text classification. It is also known that globalisation techniques play an important role in ... -
Empowered chaotic local search-based differential evolution algorithm with entropy-based hybrid objective function for brain tumor segmentation
Aydemir, Salih Berkan; Onay, Funda Kutlu; Yalcin, Emre (Elsevier Sci Ltd, 2024)In neuro-oncology, the precise segmentation of brain tumors from Magnetic Resonance Images is crucial for diagnosis, treatment planning, and monitoring disease progression. Accurate segmentation helps determine the tumor's ... -
Enhanced marine predator algorithm for global optimization and engineering design problems
Aydemir, Salih Berkan (Elsevier Sci Ltd, 2023)Marine predator algorithm adopts the policy of optimal encounter rate in biological interaction between predator and prey, inspired by the Levy and Brownian motions commonly used in oceanic predators. However, the Marine ... -
Extreme Learning Machine Algorithms for Prediction of Positive Rate in Covid-19: A Comparative Study
Various pandemics have been recorded in world history until today. The Covid-19 outbreak, which emerged at the end of 2019, has recently been a hot topic in the literature. In this work, extreme learning algorithms are ... -
Ideal solution candidate search for starling murmuration optimizer and its applications on global optimization and engineering problems
Aydemir, Salih Berkan (Springer, 2023)In this article, a novel population selection method, fitness distance balance (FDB), and predictive candidate (PC) solution generation hybridization with starling murmuration optimizer (SMO), FDBPC-SMO are proposed. In ... -
Improved honey badger algorithms for parameter extraction in photovoltaic models
Duzenli, Timur; Onay, Funda Kutlu; Aydemir, Salih Berkan (Elsevier Gmbh, 2022)Precise estimation of the parameter values of solar models is very essential for optimization of solar systems. Many studies that use metaheuristic algorithms have recently been proposed for parameter estimation and ... -
Küresel Optimizasyon için Gauss Kaotik Haritası ile Kartal Optimizasyonu
Aydemir, Salih Berkan (2022)Bu çalışmada, Gauss kaotik haritası, kartal (Aquila) optimizasyon algoritmasındaki rastgele değişkenlerin yerine kullanılmaktadır. Kaotik haritaların tekrar edilememezlik özelliği ile küresel optimum noktaya yakınsama ... -
Marine predator algorithm with elite strategies for engineering design problems
Aydemir, Salih Berkan; Onay, Funda Kutlu (Wiley, 2023)Marine predator algorithm (MPA) is a powerful metaheuristic optimization algorithm that shows effective convergence ability on complex benchmark functions. The combination of Brownian and Levy flight distributions directly ... -
A novel arithmetic optimization algorithm based on chaotic maps for global optimization
Aydemir, Salih Berkan (Springer Heidelberg, 2023)Chaotic maps are effective in developing evolutionary algorithms (EAs) to avoid local optima and speed convergence. Because of this capability of chaotic maps, these maps have been hybridized with various optimization ... -
A novel version of slime mould algorithm for global optimization and real world engineering problems Enhanced slime mould algorithm
Ornek, Bulent Nafi; Aydemir, Salih Berkan; Duzenli, Timur; Ozak, Bilal (Elsevier, 2022)The slime mould algorithm is a stochastic optimization algorithm based on the oscillation mode of nature's slime mould, and it has effective convergence. On the other hand, it gets stuck at the local optimum and struggles ... -
Power Muirhead mean in spherical normal fuzzy environment and its applications to multi-attribute decision-making Spherical normal fuzzy power Muirhead mean
Temel, Tansu; Aydemir, Salih Berkan; Hoscan, Yasar (Springer Heidelberg, 2022)This study aims to propose the power Muirhead mean (PMM) operator in the spherical normal fuzzy sets (SNoFS) environment to solve multiple attribute decision-making problems. Spherical normal fuzzy sets better characterize ... -
Some remarks on activation function design in complex extreme learning using Schwarz lemma
Ornek, Bulent Nafi; Aydemir, Salih Berkan; Duzenli, Timur; Ozak, Bilal (Elsevier, 2022)Processing of complex valued data has become a challenge issue in classification problems where artificial neural networks are used as the classifier. This issue particularly arises in design of complex valued activation ... -
Tropospheric zenith wet delay prediction with a new hybrid ANN-Gorilla troops optimizer algorithm
Konakoglu, Berkant; Onay, Funda Kutlu; Aydemir, Salih Berkan (Elsevier Sci Ltd, 2023)In recent years, machine learning techniques, especially artificial neural networks (ANN), have been widely applied for engineering problems since they have proven to be a good predictor, especially in accurate weather ...
