Erdal Eker
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View article: Metaheuristic-Driven Optimization of a Neural Model Using Tuna Swarm Intelligence for Cognitive Classification of Wheat Species
Metaheuristic-Driven Optimization of a Neural Model Using Tuna Swarm Intelligence for Cognitive Classification of Wheat Species Open
Accurate classification of wheat varieties is vital for enhancing agricultural productivity and maintaining food quality standards. However, conventional methods based on manual inspection are time-consuming, labor-intensive, and prone to …
View article: A Novel 2-DOF PIDA control strategy with GCRA-based parameter optimization for electric furnace temperature control
A Novel 2-DOF PIDA control strategy with GCRA-based parameter optimization for electric furnace temperature control Open
Accurate and energy-efficient temperature regulation in electric furnace systems remains a challenging control problem due to nonlinear dynamics, significant thermal inertia, and inevitable time delays. Conventional proportional–integral–d…
View article: Improvement of Wild Horse Optimizer Algorithm with Random Walk Strategy (IWHO), and Appointment as MLP Supervisor for Solving Energy Efficiency Problem
Improvement of Wild Horse Optimizer Algorithm with Random Walk Strategy (IWHO), and Appointment as MLP Supervisor for Solving Energy Efficiency Problem Open
This paper aims to enhance the success of the Wild Horse Optimization (WHO) algorithm in optimization processes by developing strategies to overcome the issues of stuckness and early convergence in local spaces. The performance change is o…
View article: Development of Random Walks Strategy-Based Dandelion Optimizer and Its Application to Engineering Design Problems
Development of Random Walks Strategy-Based Dandelion Optimizer and Its Application to Engineering Design Problems Open
The objective of this paper is to enhance the swarm-based metaheuristic dandelion optimizer (DO) algorithm by incorporating various strategies to address early convergence and mitigate the risk of becoming trapped in local optima. This int…
View article: Enhanced RSA Optimized TID Controller for Frequency Stabilization in a Two-Area Power System
Enhanced RSA Optimized TID Controller for Frequency Stabilization in a Two-Area Power System Open
This study presents an enhanced reptile search algorithm (ImRSA) optimized tilt-integral-derivative (TID) controller for load frequency control (LFC) in a two-area power system consisting of photovoltaic (PV) and thermal power units. The I…
View article: Performance evaluation of logarithmic spiral search and selective mechanism based arithmetic optimizer for parameter extraction of different photovoltaic cell models
Performance evaluation of logarithmic spiral search and selective mechanism based arithmetic optimizer for parameter extraction of different photovoltaic cell models Open
The imperative shift towards renewable energy sources, driven by environmental concerns and climate change, has cast a spotlight on solar energy as a clean, abundant, and cost-effective solution. To harness its potential, accurate modeling…
View article: Optimization of Non-Linear Problems Using Salp Swarm Algorithm and Solving the Energy Efficiency Problem of Buildings with Salp Swarm Algorithm-based Multi-Layer Perceptron Algorithm
Optimization of Non-Linear Problems Using Salp Swarm Algorithm and Solving the Energy Efficiency Problem of Buildings with Salp Swarm Algorithm-based Multi-Layer Perceptron Algorithm Open
The aim of this paper is to evaluate the optimization capabilities of the salp swarm algorithm (SSA), a metaheuristic algorithm capable of addressing contemporary global challenges. The paper focuses on assessing SSA as an optimizer and ob…
View article: Performance Evaluation of Capuchin Search Algorithm Through Non-linear Problems, and Optimization of Gear Train Design Problem
Performance Evaluation of Capuchin Search Algorithm Through Non-linear Problems, and Optimization of Gear Train Design Problem Open
The purpose of this paper is to demonstrate the superiority of the Capuchin Search Algorithm (CapSA), a metaheuristic, in competitive environments and its advantages in optimizing engineering design problems. To achieve this, the CEC 2019 …
View article: Comparison of Swarm-based Metaheuristic and Gradient Descent-based Algorithms in Artificial Neural Network Training
Comparison of Swarm-based Metaheuristic and Gradient Descent-based Algorithms in Artificial Neural Network Training Open
This paper aims to compare the gradient descent-based algorithms under classical training model and swarm-based metaheuristic algorithms in feed forward backpropagation artificial neural network training. Batch weight and bias rule, Bayesi…
View article: Optimal PID Controller Design for Liquid Level Tank via Modified Artificial Hummingbird Algorithm
Optimal PID Controller Design for Liquid Level Tank via Modified Artificial Hummingbird Algorithm Open
To enhance controller performance, the optimization of control parameters has emerged as a critical research area. Among the array of optimization algorithms, the modified elite opposition-based artificial hummingbird algorithm (m-AHA) sta…
View article: Performance Evaluation of PDO Algorithm through Benchmark Functions and MLP Training
Performance Evaluation of PDO Algorithm through Benchmark Functions and MLP Training Open
Metaheuristic algorithms have become very common in the last two decades. The flexibility and ability to overcome obstacles in solving global problems have increased the use of metaheuristic algorithms. In the training of multilayer percep…
View article: Assessment of GTO: Performance evaluation via constrained benchmark function, and Optimized of Three Bar Truss Design Problem
Assessment of GTO: Performance evaluation via constrained benchmark function, and Optimized of Three Bar Truss Design Problem Open
The aim of this paper is to show that the artificial gorilla troops optimization (GTO) algorithm, as an optimizer, can cope with test functions such as CEC2019, and also to best optimize the three bar truss design problem as a constrained …
View article: SCANM: A Novel Hybrid Metaheuristic Algorithm and Its Comparative Performance Assessment
SCANM: A Novel Hybrid Metaheuristic Algorithm and Its Comparative Performance Assessment Open
This paper proposes a novel sine-cosine and Nelder-Mead (SCANM) algorithm which hybridizes the sine-cosine algorithm (SCA) and Nelder-Mead (NM) local search method. The original version of SCA is prone to early convergence at the local min…
View article: Augmented hunger games search algorithm using logarithmic spiral opposition-based learning for function optimization and controller design
Augmented hunger games search algorithm using logarithmic spiral opposition-based learning for function optimization and controller design Open
This paper explains the construction of a novel augmented hunger games search algorithm using a logarithmic spiral opposition-based learning technique. The proposed algorithm (LsOBL-HGS) is used as an efficient tool for both function optim…
View article: A Novel Enhanced Metaheuristic Algorithm for Automobile Cruise Control System
A Novel Enhanced Metaheuristic Algorithm for Automobile Cruise Control System Open
The development of a novel enhanced metaheuristic algorithm is considered in this paper. Such a structure was achieved through enhancement of the arithmetic optimization algorithm by employing the opposition-based learning mechanism togeth…
View article: A Novel Modified Lévy Flight Distribution Algorithm based on Nelder-Mead Method for Function Optimization
A Novel Modified Lévy Flight Distribution Algorithm based on Nelder-Mead Method for Function Optimization Open
This paper aims to improve one of the recently proposed metaheuristic approaches known as Lévy flight distribution (LFD) algorithm by adopting a well-known simplex search algorithm named Nelder-Mead (NM) method. Three new strategies were u…