Optimized Real-Time Energy Management and Neural Network-Based Control for Photovoltaic-Integrated Hybrid Uninterruptible Power Supply Systems by Ruben Rafael Boros, Marcell Jobbágy, István Bodnár

“…Additionally, a genetic algorithm is implemented to optimize the power sharing ratio, minimizing the LCOE under varying load and electricity pricing conditions. …”
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Embedded Rough-Neck Helmholtz Resonator Low-Frequency Acoustic Attenuator by Xianming Sun, Tao Yu, Lipeng Wang, Yunshu Lu, Changzheng Chen

“…Moreover, by coupling the BP network with the Golden Jackal Optimization (GJO) algorithm, a BP-GJO optimization model is developed to refine the structural parameters. …”
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A multi task learning framework using DeBERTa and BWO optimization for enhancing long term english vocabulary memory by Jiasheng Zhu

“…This study shows that the BWO-optimized DeBERTa multi-task learning model can effectively improve the long-term memory retention of English words and has stronger anti-interference ability in complex memory environments.…”
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Migraine triggers, phases, and classification using machine learning models by Anusha Reddy, Ajit Reddy

“…These models are run with the dataset without optimal tuning across the entire dataset for different migraine types; which is further improved with selective sampling and optimal tuning. …”
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An Optimal Energy Management Strategy With Time-Varying Equivalent Factor Based on Transformer for Multi-Mode Hybrid Electric Mining Trucks by Xinxin Zhao, Jiaqi Li, Menglei Liu, Jinggang Zhang, Nasser Lashgarian Azad

“…This paper introduces an advanced Transformer network model aimed at an adaptive Energy Management Strategy (EMS) to improve the fuel efficiency of Hybrid Electric Mining Trucks (HEMTs). …”
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Efficiency assessment of micro hydropower for agriculture using modern modeling by Urishev Omadjon, Salomov Uktam, Ergashev Sirojiddin, Kuchkarov Akmaljon, Madaliev Murodil, Abdukarimov Bekzod, Juraev Nurmakhamad

“…Using modern numerical analysis methods, including computational turbulence modeling algorithms, the study evaluates the energy production and optimization of micro-hydropower plant operation under various conditions. …”
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Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…Further, the selection of features is performed by DBO algorithm, which removes redundant features and helps to improve efficiency and accuracy. …”
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Improving resectable gastric cancer prognosis prediction: A machine learning analysis combining clinical features and body composition radiomics by Gianni S.S. Liveraro, Maria E.S. Takahashi, Fabiana Lascala, Luiz R. Lopes, Nelson A. Andreollo, Maria C.S. Mendes, Jun Takahashi, José B.C. Carvalheira

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Machine Learning with Evolutionary Parameter Tuning for Singing Registers Classification by Tales Boratto, Gabriel de Oliveira Costa, Alexsandro Meireles, Anna Klara Sá Teles Rocha Alves, Camila M. Saporetti, Matteo Bodini, Alexandre Cury, Leonardo Goliatt

“…Thus, the present article proposes a novel approach that leverages the Differential Evolution (DE) algorithm to optimize hyperparameters within three selected ML models, with the aim of classifying singing-voice registers i.e., chest, mixed, and head registers). …”
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A hybrid simple exponential smoothing-barnacles mating optimization approach for parameter estimation: Enhancing COVID-19 forecasting in Malaysia by Azlan Abdul Aziz, Zuriani Mustaffa, Suzilah Ismail, Nor Azriani Mohamad Nor, Nurin Qistina Mohamad Fozi

“…Therefore, this study aims to propose a new hybrid model, the Single Exponential Smoothing (SES)-Barnacles Mating Optimization (BMO) algorithm, to estimate the optimal smoothing parameter alpha and initial value that can improve the percentage of forecast accuracy. …”
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Quality Prediction Model Based on Novel Elman Neural Network Ensemble by Lan Xu, Yuting Zhang

“…In this paper, we propose a novel prediction algorithm based on an improved Elman neural network (NN) ensemble for quality prediction, thus achieving the quality control of designed products at the product design stage. …”
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Modeling and Control of Permanent Magnet Synchronous Motor Based Electric Vehicle by Rajesh G., K. Sebasthirani

“…The research focuses on the design and optimization of Fractional Order PID (FOPID) controllers, leveraging Genetic Algorithm (GA) and Hybrid Reinforcement Genetic Algorithm-Recursive Backpropagation Learning (GA-RBL) techniques to enhance tuning performance. …”
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A multitasking ant system for multi-depot pick-up and delivery location routing problem with time window by Haoyuan Lv, Ruochen Liu, Jianxia Li

“…Furthermore, ignoring the potential general knowledge among different schemes leads to redundant optimization. In this work, MDPDLRPTW is modeled as a multi-transformation optimization (MTFO) problem and a novel two-stage algorithm based on multitasking ant system (MTAS) is designed to solve it. …”
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River floating object detection with transformer model in real time by Chong Zhang, Jie Yue, Jianglong Fu, Shouluan Wu

“…Our experimental findings are compelling: LR-DETR achieves a 5% increase in mean Average Precision (mAP) at an Intersection over Union (IoU) threshold of 0.5, a 25.8% reduction in parameter count, and a 22.8% decrease in GFLOPs, compared to the RT-DETR algorithm. These improvements are particularly pronounced in the real-time detection of river floating objects, showcasing LR-DETR’s potential in specific environmental monitoring scenarios. …”
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A novel and sturdy MPPT architecture for grid-tied EV charging stations using Ali Baba and forty thieves optimization by Debabrata Mazumdar, Hassan Abdurrahman Shuaibu, Chiranjit Sain, Taha Selim Ustun

“…This approach aims to optimize modelling for all EV fleets. The developed method performs exceptionally well in comparison to other algorithms that have been studied in the literature. …”
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Establishment of Hyperspectral Prediction Model of Water Content in Anshan-Type Magnetite by Xiaoxiao XIE, Yang BAI, Jiuling ZHANG, Yuna JIA

“…Using S-G smoothing filtering (S-G), multivariate scattering correction (MSC), standard normal transformation (SNV), second derivative (SD), reciprocal logarithm (LR) and continuum removal (CR) to preprocess the data, the spectral characteristics and their correlation with water content were analyzed. In order to further improve the prediction ability of the model, the competitive adaptive reweighting method (CARS) was used to optimize the characteristic band, and a prediction model was established by combining random forest regression (RFR), least squares support vector regression (LSSVR) and particle swarm optimization least squares support vector regression (PSO-LSSVR). …”
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Spatial distribution prediction of pore pressure based on Mamba model by Xingye Liu, Xingye Liu, Bing Liu, Wenyue Wu, Qian Wang, Yuwei Liu

“…The model is a structured state-space model designed to process complex time-series data, and improve efficiency through parallel scan algorithm, making it suitable for large-scale three-dimensional data prediction. …”
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Simulation-Based Design and Machine Learning Optimization of a Novel Liquid Cooling System for Radio Frequency Coils in Magnetic Hyperthermia by Serhat Ilgaz Yöner, Alpay Özcan

“…Sensitivity analysis and the ReliefF algorithm were applied for a thorough analysis. Simulation results indicate that the proposed novel liquid cooling system demonstrates higher performance compared to conventional systems that utilize direct liquid cooling, offering a computationally efficient method for pre-manufacturing design optimization of radio frequency coil cooling systems in magnetic hyperthermia applications.…”
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Optimizing solar maximum power point tracking with adaptive PSO: A comparative analysis of inertia weight and acceleration coefficient strategies by Denesh Sooriamoorthy, Aaruththiran Manoharan, Siva Kumar Sivanesan, Soon Kian Lun, Alexander Chee Hon Cheong, Sathish Kumar Selva Perumal

“…Metaheuristic algorithms such as Particle Swarm Optimization (PSO) are explored extensively for MPPT applications. …”
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Early Parkinson’s disease identification via hybrid feature selection from multi-feature subsets and optimized CatBoost with SMOTE by Subhashree Mohapatra, Bhanja Kishor Swain, Manohar Mishra

“…The proposed framework leverages a strong categorical boosting (CatBoost) algorithm optimized using Grid Search Optimization (GSO). …”
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