Optimal Placement of Phasor Measurement Unit in Electrical Grid Using Dingo Optimization Algorithm by ARIYO Funso Kehinde, AYANLADE Samson Oladayo, JIMOH Abdulrasaq, ADEBAYO Moses Taiwo

“…The study utilizes the Dingo Optimization Algorithm, a metaheuristic inspired by nature, to identify the best PMU placement. …”
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A Projection Strategy for Improving the Preconditioner in the LOBPCG by Ma Tailai, Sun Shuli, Zheng Fangyi, Chen Pu

“…This oblique projection technique can find a more accurate approximate solution which minimizes the 2-norm residuals in the search subspace without significantly increasing computational cost, thereby improving the quality of the preconditioner, thus accelerating convergence of the LOBPCG.Numerical experiments show that the projection strategy can improve the LOBPCG algorithm significantly in terms of efficiency and stability.…”
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A Gradient-Based Optimization Algorithm for Optimal Control Problems With General Conformable Fractional Derivatives by Essia Ben Alaia, Slim Dhahri, Omar Naifar

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A new sliding mode control strategy to improve active power management in a laboratory scale microgrid by Oscar Gonzales-Zurita, Jean-Michel Clairand, Guillermo Escrivá-Escrivá

“…This study proposes a robust control solution based on the second-order sliding mode control (SMC-2) algorithm to overcome the mentioned challenges. This algorithm employed a non-conventional sliding surface to improve the microgrid’s capacities for energy management. …”
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Multi strategy Horned Lizard Optimization Algorithm for complex optimization and advanced feature selection problems by Marwa M. Emam, Mosa E. Hosney, Reham R. Mostafa, Essam H. Houssein

“…However, when applied to high-dimensional datasets characterized by a vast number of features and limited samples-these methods often suffer from performance degradation and increased computational costs. The Horned Lizard Optimization Algorithm (HLOA) is a nature-inspired metaheuristic that mathematically mimics the adaptive defense mechanisms of horned lizards, including crypsis, skin color modulation, blood-squirting, and escape movements. …”
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DEVELOPMENT OF THE ALGORITHM FOR CHOOSING THE OPTIMAL SCENARIO FOR THE DEVELOPMENT OF THE REGION'S ECONOMY by I. S. Borisova

“…It was found that the rationale and choice of the optimal scenario is an important stage in the development of the sustainable development program of the regional economy, since it helps to quantify the most probable trajectories of changes in the activities of all participants in the region's economy.Conclusions and Relevance: the practical significance of the developed algorithm lies in the possibility of using it to improve the stability of the development of the economy of specific regions. …”
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Optimization of machine learning algorithms for proteomic analysis using topsis by Javanbakht T., Chakravorty S.

“…The present study focuses on a new application of the TOPSIS method for the optimization of machine learning algorithms, supervised neural networks (SNN), the quick classifier (QC), and genetic algorithm (GA) for proteomic analysis. …”
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(IoT) Network intrusion detection system using optimization algorithms by Luo Shan

“…Abstract To address the complex requirements of network intrusion detection in IoT environments, this study proposes a hybrid intelligent framework that integrates the Whale Optimization Algorithm (WOA) and the Grey Wolf Optimization (GWO) algorithm—referred to as WOA-GWO. …”
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Detection of Plants Leaf Diseases using Swarm Optimization Algorithms by Saud Abdul Razzaq, Baydaa Khaleel

“…In this paper, a new method is proposed to classify and distinguish a group of eight different plants to healthy and unhealthy based on the leaf images of these plants They are apples, cherries, grapes, peaches, peppers, potatoes, strawberries, and tomatoes using a hybrid optimization algorithm. In the first stage, the plant leaf images were collected and pre-processed to remove noise and improve contrast. …”
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Offshore Wind Farm Layout Optimization Considering the Power Collection System Cost by S. G. Obukhov, D. Y. Davydov

“…The change in the size and shape of the boundaries of the wind farm site resulted in an increase in the estimated electricity generation by 2.3 % and a decrease in its cost by 4 %. When optimizing the layout of wind turbines within the fixed boundaries of the site, these indicators are improved by only 1 and 2 % as compared to the original scheme.…”
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A Review of Stochastic Optimization Algorithms Applied in Food Engineering by Laís Koop, Nadia Maria do Valle Ramos, Adrián Bonilla-Petriciolet, Marcos Lúcio Corazza, Fernando Augusto Pedersen Voll

“…It was observed that evolutionary methods are the most applied in solving food engineering optimization problems where the genetic algorithm and differential evolution stand out. …”
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Optimal geometrical selection of skin mesh: experimental analysis and numerical optimization by Mehdi Khayami, Aisa Rassoli, Alireza Feizkhah

“…Hyperelastic properties of healthy and meshed skin were obtained through uniaxial tensile tests, and different geometries were analyzed using Abaqus. The optimal mesh geometry was then determined using genetic algorithms in Abaqus and MATLAB. …”
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Operation Optimization Strategy of Commercial Combined Electric Heating System Based on Particle Swarm Optimization Algorithm by WANG Qing, LI Congcong, WANG Pingxin, WU Qingqing, CAI Xiaoyu

“… In order to improve the energy efficiency of the electric heating system, a particle swarm optimization (PSO, Particle Swarm Optimization)-based operation optimization strategy for the direct storage combined electric heating system is proposed.A mathematical model of influencing factors inside and outside the walls of electric heating buildings is established, and the simulink toolbox in matlab is used to build the overall system under the premise of determining the quantity of electric heating.Combining demand response ideas, the objective function is to establish the minimum heating and electricity cost of the user, and different sub-modules are selected to form the control module to achieve simulation verification, and the inverse cosine method is used to update the improved particle swarm algorithm to update the learning factor to solve the set objective function.Finally, through a calculation example of electricity consumption data of an enterprise in Jinan, Shandong, comparing energy consumption and economy can be obtained: the total energy consumption throughout the day is lower than the actual energy consumption, and the electricity bill is reduced by 17.16% compared with the unoptimized time.…”
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Application of Swarm Intelligence Optimization Algorithm in Logistics Delivery Path Optimization under the Background of Big Data by Guofu Zhao

“…The hybrid algorithm can effectively improve the optimization efficiency of VRPTW, lay a foundation for solving large-scale VRPTW, and provide new research ideas and methods. …”
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Adaptive Multi-Objective Firefly Optimization for Energy-Efficient and QoS-Aware Scheduling in Distributed Green Data Centers by Ahmed Chiheb Ammari, Wael Labidi, Rami Al-Hmouz

“…To solve this, we propose an Adaptive Firefly-Based Bi-Objective Optimization (AFBO) algorithm that introduces multiple adaptive mechanisms to improve convergence and diversity. …”
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The Improved MNSPI Method for MODIS Surface Reflectance Data Small-Area Restoration by Meixiang Wang, Wenjuan Zhang, Bowen Wang, Xuesong Ma, Peng Qi, Zixiang Zhou

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An improved lightweight method based on EfficientNet for birdsong recognition by Haolun He, Hui Luo

“…Finally, we employ the Adam optimization algorithm to improve network convergence speed. …”
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Identifying Capsule Defect Based on an Improved Convolutional Neural Network by Junlin Zhou, Jiao He, Guoli Li, Yongbin Liu

“…The improved CNN algorithm is based on regularization and the Adam optimizer (RACNN), on which a dropout layer and L2_regularization are added between the full connection and the output layer to solve the overfitting problem. …”
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RRMSE-enhanced weighted voting regressor for improved ensemble regression. by Shikun Chen, Wenlong Zheng

“…This uniform weighting approach doesn't consider that some models may perform better than others on different datasets, leaving room for improvement in optimizing ensemble performance. To overcome this limitation, we propose the RRMSE (Relative Root Mean Square Error) Voting Regressor, a new ensemble regression technique that assigns weights to each base model based on their relative error rates. …”
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Provide a method to diagnose and optimize diabetes using data mining methods and firefly algorithm by Reza Molaee Fard

“…Diabetes is one of the most common, dangerous and costly diseases in the world today, which is increasing at an alarming rate. …”
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