Improved Genetic Algorithm-Based Harmonic Mitigation Control of an Asymmetrical Dual-Source 13-Level Switched-Capacitor Multilevel Inverter by Hasan Iqbal, Arif Sarwat

“…A single-phase multilevel inverter with a switched-capacitor multilevel (SC-MLI) configuration is developed to provide 13-level output voltages. An improved genetic algorithm (GA) with adaptive mutation and crossover rates is employed to achieve robust harmonic mitigation by avoiding local optima and ensuring optimal performance. …”
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A new smart charging electric vehicle and optimal DG placement in active distribution networks with optimal operation of batteries by Bilal Naji Alhasnawi, Marek Zanker, Vladimír Bureš

“…Thirdly, this paper proposes an optimization technique based on the Mountain Gazelle Optimizer (MGO), Improved Beluga Whale Optimization (IBWO), and Arithmetic Optimization Algorithm (AOA) for determining the optimal DGs in radial distribution systems. …”
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FAULT DIAGNOSIS METHOD OF SUBMERSIBLE SEWAGE PUMP BASED ON IMPROVED HOPFIELD NEURAL NETWORK by WANG Hui, LI NanQi, YANG ZhiPeng, ZHAO GuoChao, TIAN LiYong

“…The connection weights of HNN neural network were optimized by particle swarm optimization（PSO） algorithm to improve the global convergence ability of the improved neural network, and the improved HNN neural network model was obtained. …”
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Auto-Tuning Memory-Based Adaptive Local Search Gaining–Sharing Knowledge-Based Algorithm for Solving Optimization Problems by Nawaf Mijbel Alfadli, Eman Mostafa Oun, Ali Wagdy Mohamed

“…This selection process is guided by a weighted moving average that tracks each parameter’s contribution to fitness improvement over time. To further reduce the risk of premature convergence, an adaptive local search strategy is embedded, facilitating the algorithm’s escape from local traps and guiding it toward more optimal regions within the search domain. …”
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Comparative Analysis of Some Methods and Algorithms for Traffic Optimization in Urban Environments Based on Maximum Flow and Deep Reinforcement Learning by Silvia Baeva, Nikolay Hinov, Plamen Nakov

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Multi-Target Firefighting Task Planning Strategy for Multiple UAVs Under Dynamic Forest Fire Environment by Pei Zhu, Shize Jiang, Jiangao Zhang, Ziheng Xu, Zhi Sun, Quan Shao

“…In this process, the study considers only the use of fire-extinguishing balls as the fire suppressant for the UAVs. The improved multi-population grey wolf optimization (MP–GWO) algorithm and non-Dominated sorting genetic algorithm II (NSGA-II) were designed to solve the path planning and task allocation models, respectively. …”
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A novel hybrid approach for thyroid disease detection: Integrating cuttlefish algorithm and simulated annealing for optimal feature selection by Kapil Shrivastava, Saroj Pandey, Rishav Dubey, Mayank Namdev, Vipin Tiwari, Aditi Sharma

“…This study advances medical diagnostics by combining machine learning algorithms with nature-inspired optimization techniques to detect thyroid illnesses in their early stages. • This article proposes a novel hybrid algorithm that combines the Cuttlefish Optimization Algorithm (CFA) and Simulated Annealing (SA) to find the best features for finding thyroid disease. • The study uses machine-learning models for classification. • The integration of machine learning and nature-inspired optimization significantly enhances the diagnostic capabilities of healthcare systems, enabling prompt diagnosis and treatment planning for thyroid disorders.…”
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Enhancing phishing detection with dynamic optimization and character-level deep learning in cloud environments by Vishnukumar Ravula, Mangayarkarasi Ramaiah

“…To address these emerging threats, this study introduces a novel Dynamic Arithmetic Optimization Algorithm with Deep Learning-Driven Phishing URL Classification (DAOA-DLPC) model for cloud-enabled IoV infrastructure. …”
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A novel swarm intelligence-based approach for solving optimal power flow problems in modern power systems by Haewon Byeon, Wajdi Alghamdi, Munni Evin, M. Sucharitha, D. David Neels Ponkumar, A. Prakash, J. Sunil

“…In order to solve the optimum power flow difficulties related to the C-UPFC, this research suggested an Improved Pelican optimization algorithm (IPOA). Install the superior flexible AC transmission system (FACTS) in accordance with the transmission line (TL) in a series configuration to provide independent voltage control that combines power flow regulation. …”
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Multijunction solar cell parameter estimation based on metaheuristic algorithms by Marwa M. Elzalabani, Doaa M. Atia, Aref Y. Eliwa, Belal A. Abou Zalam, Mahmoud S. AbouOmar

“…The study compared the performance of five optimization algorithms: Grey Wolf Optimizer (GWO), Artificial Hummingbird Algorithm (AHA), Tunicate Swarm Algorithm (TSA), War Strategy Algorithm (WSA), and Moth flam optimizer (MFO). …”
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Optimization of Vehicles Routing Problem using GA For AL-Rasheed municipality, Baghdad, Iraq by zainab talib, Muayed Al-Huseiny

“…The current study's objective is to apply a genetic algorithm to reach the goals, illustrating the process of selecting the optimal route for the vehicle with the lowest time and greatest weight among several paths. …”
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A Methodology to Characterize an Optimal Robotic Manipulator Using PSO and ML Algorithms for Selective and Site-Specific Spraying Tasks in Vineyards by Roni Azriel, Oded Degani, Avital Bechar

“…It compares the current approach for optimizing manipulator configurations, which relies on simulation and optimization algorithms, with an improved methodology that integrates machine learning models to enhance the optimization process. …”
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Bearing fault diagnosis for high-speed train based on improved VMD and APSO-SVM by ZHANG Qingsong, ZHANG Bing, QIN Yi

“…The experimental results show that traditional SVM has better effect on the diagnosis of rolling element fault and composite type fault, but the diagnosis effect on cage fault is relatively poor. Therefore, APSO algorithm was used to optimize the core parameters of the SVM, which further improved the recognition accuracy of cage fault and realized the effective identification for the fault bearings of high-speed train.…”
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Novel concept for the healthy population influencing factors by Yuhao Shen, Jichao Wang, Lihua Ma, Huizhe Yan

“…Community analysis divides the floating population into different health records and promotes targeted intervention measures. The random forest model improves the accuracy and universality of predictions. …”
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A Bi-Level Optimization Scheme for Energy Storage Configuration in High PV-Penetrated Distribution Networks Based on Improved Voltage Sensitivity Strategy by Bo Gao, Qing Du, Gonghao Zhan, Jian Han

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An Efficient Mutual Authentication and Fractional Lyrebird Optimization With Deep Learning–Based SIP-Based DRDoS Attack Detection by V. Sreenivasulu, C. V. Ravikumar

“…In this article, a deep learning model fractional lyrebird optimization algorithm–deep stack autoencoder (FLOA-DSA) is developed for the detection of SIP-based distributed reflection denial-of-service (DRDoS) attacks in SIP network. …”
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Indirect tuning of a complementary orientation filter using velocity data and a genetic algorithm by Dariusz Maton, John T. Economou, David Galvão Wall, Irfan Khan, Robert Cooper, David Ward, Simon Trythall

“…In this paper, the accuracy of inertial sensor orientation relative to the level frame is improved through optimal tuning of a complementary filter by a genetic algorithm. …”
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Comparative Study on Hyperparameter Tuning for Predicting Concrete Compressive Strength by Jeonghyun Kim, Donwoo Lee

“…This study assesses the impact of hyperparameter optimization algorithms on the performance of machine learning-based concrete compressive strength prediction models. …”
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Feature engineering through two-level genetic algorithm by Aditi Gulati, Armin Felahatpisheh, Camilo E. Valderrama

“…Feature engineering can enhance the performance of interpretable models by identifying features that optimize classification. …”
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Distribution Generation Network Arrangement by Capacitor Placement and Sizing in Renewable Energy Sources with Uncertainties Based on Self-adaption Kho-Kho Optimizer by Lu Xingxing

“…Post-optimization results indicated a reduction in power loss costs from 4.11 × 10^5 to 1.05 × 10^5 units, representing a 25.54% decrease. …”
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