Optimizing Hyperparameters in Meta-Learning for Enhanced Image Classification by Amala Mary Vincent, P. Jidesh, A. A. Bini

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An investigation into multi-objective decision-making in fresh cold chain supply chain networks within a dual distribution framework by Junyan Sun, Xing Li, Zefei Chen

“…The algorithm results show that, compared to the traditional NSGA-II and the SA-NSGA-II algorithms with random initialization, the LHS-SA-NSGA-II algorithm demonstrates clear advantages in terms of total cost, carbon emissions, and distribution time, confirming its superiority in optimizing cold chain networks. …”
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Optimization of a Coupled Neuron Model Based on Deep Reinforcement Learning and Application of the Model in Bearing Fault Diagnosis by Shan Wang, Jiaxiang Li, Xinsheng Xu, Ruiqi Wu, Yuhang Qiu, Xuwen Chen, Zijian Qiao

“…By comparing the coupled neuron model optimized with a reinforcement learning algorithm, particle swarm algorithm, and quantum particle swarm algorithm, the experimental results show that the coupled neuron model optimized with a deep reinforcement learning algorithm has the optimal signal-to-noise ratio of the output signal and recognition rate of the bearing faults, which are −13.0407 dB and 100%, respectively. …”
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Leveraging prior mean models for faster Bayesian optimization of particle accelerators by Tobias Boltz, Jose L. Martinez, Connie Xu, Kathryn R. L. Baker, Zihan Zhu, Jenny Morgan, Ryan Roussel, Daniel Ratner, Brahim Mustapha, Auralee L. Edelen

“…Abstract Tuning particle accelerators is a challenging and time-consuming task that can be automated and carried out efficiently using suitable optimization algorithms, such as model-based Bayesian optimization techniques. …”
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Optimizing precision farming: enhancing machine learning efficiency with robust regression techniques in high-dimensional data by Nour Hamad Abu Afouna, Majid Khan Majahar Ali

“… Smart precision farming leverages IoT, cloud computing, and big data to optimize agricultural productivity, lower costs, and promote sustainability through digitalization and intelligent methodologies. …”
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Research on cutting mechanism and process optimization method of gear skiving by Peng Wang, Yuanchao Ni, Xiaoqiang Wu, Jiaxue Ji, Geng Li, Jiahao Wu

“…Furthermore, a prediction model of cutting force and cutting temperature is established using a neural network optimized by genetic algorithm. …”
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Numerical modeling and neural network optimization for advanced solar panel efficiency by Udit Mamodiya, Indra Kishor, Mohammed Amin Almaiah, Monia Hamdi, Rami Shehab, Tayseer Alkhdour

“…Conventionally, such optimization techniques—MPPT (Maximum Power Point Tracking) along with heuristic algorithms—suffer significantly from slow adaptability and track sub optimality under dynamic environments. …”
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Small-Signal Stability Analysis and Parameters Optimization of Virtual Synchronous Generator for Low-Inertia Power System by Alaa Altawallbeh, Abdulrahman Alassi, Nader Meskin, Mohammed A. Al-Hitmi, Ahmed M. Massoud

“…We further propose a hybrid Particle Swarm Optimization (PSO) algorithm with a multi-objective cost function to optimize VSG controller gains. …”
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Research on the method of weight calculation and equipment arrangement optimization of tramcar by DUAN Huadong, LIU Xiaofeng, JIANG Zhongcheng, ZHANG Bo

“…Based on Isight optimization platform, multi-objective optimization algorithm was adopted to improve the equipment layout. …”
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Synergistic integration of refined pelican optimization algorithm and deep neural networks for autonomous vehicle control in edge computing architectures by Fude Duan, Bing Han, Xiongzhu Bu

“…The chief contributions of the present study have been threefold: (1) the improvement of a particular autonomous driving method optimized for mobile edge computing platforms; (2) the arrangement of an optimized MobileNet method employing the RPO algorithm that uses LiDAR sensor data for effective object recognition and path design; and (3) the construction of an indoor vehicle prototype by mean of a microcontroller and LiDAR sensors, after a comprehensive performance evaluation of inference models, and analyzing the trade-offs between input size and computational effectiveness. …”
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Optimal Allocation of Hybrid Renewable Distributed Generation with Battery Energy Storage System Using MOEA/D-DRA Algorithm by P. Pon Ragothama Priya, S. Baskar, S. Tamil Selvi, C. K. Babulal

“…The proposed formulation for a Multi-objective Optimization of Hybrid Energy Sources allocation problem solved by the MOEA/D-DRA algorithm provides improved benefits like minimum annual energy loss, investment cost, CO2 emission, EENS by the DG units, and enhanced system voltage stability and voltage profile.…”
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A Novel Fault Diagnosis Method for Rolling Bearing Based on Improved Sparse Regularization via Convex Optimization by Dongjie Zhong, Cancan Yi, Han Xiao, Houzhuang Zhang, Anding Wu

“…To handle this difficulty, a novel fault signal denoising scheme based on improved sparse regularization via convex optimization is proposed to extract the fault feature of rolling bearing. …”
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Research on Self-Recovery Ignition Protection Circuit for High-Voltage Power Supply System Based on Improved Gray Wolf Algorithm by Jingyi Zhu, Wanlu Zhu, Haifeng Wei, Yi Zhang

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Enhanced securities investment strategy using ISSA–SVM: a hybrid model combining adaptive moving average, support vector machine, and multi-strategy sparrow search algorithm for im... by Wei Ni, Qingqing Chen, Xiaochen Guo, Yanan Liu

“…This study proposes a novel hybrid strategy, ISSA–SVM, that combines Adaptive Moving Average (AMA), Support Vector Machine (SVM), and an Improved Sparrow Search Algorithm (ISSA) to enhance CTA model performance in securities investment. …”
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Optimized deep learning approach for lung cancer detection using flying fox optimization and bidirectional generative adversarial networks by Manal Abdullah Alohali, Hamed Alqahtani, Shouki A. Ebad, Faiz Abdullah Alotaibi, Venkatachalam K., Jaehyuk Cho

“…The methodology consists of three key phases: (1) Data preprocessing, where missing values are handled using the multiple imputations by chain equation (MICE) technique and feature scaling is applied using standard and min-max scalers; (2) Feature selection, where the FFXO algorithm reduces feature dimensionality to enhance classification efficiency; and (3) Lung tumor classification, utilizing Bi-GAN to improve predictive accuracy. …”
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Firefly algorithm with multiple learning ability based on gender difference by Wenning Zhang, Chongyang Jiao, Qinglei Zhou

“…Abstract The Firefly Algorithm (FA), while effective for complex optimization, suffers from inherent limitations such as search oscillation and low convergence precision. …”
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Application Research of Key Frames Extraction Technology Combined with Optimized Faster R-CNN Algorithm in Traffic Video Analysis by Zhi-guang Jiang, Xiao-tian Shi

“…The experimental results show that the key frame extraction technology combined with the optimized Faster R-CNN algorithm model greatly improves the accuracy of detection and reduces the leakage. …”
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Hyperparameter Optimization for Problem-Based Custom CNN Architectures Using a Smart Grid Search Method by H. Aktas

“…To classify the ripe and unripe pistachios with a small-sized and high test accuracy model, a two-layer CNN architecture’s hyperparameters were optimized with the proposed algorithm. …”
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Prediction of chloride concentration in concrete under multi-salt environment: Optimization of integrated algorithm based on MSCPO and interpretability analysis by Daming Luo, Kanglei Du, Ditao Niu

“…The Improved Mixture Self-Adaptation Crested Porcupine Optimizer (MSCPO) optimized hyperparameters for XGBoost, LightGBM, and Catboost models separately. …”
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Enhanced ANN-Based MPPT for Photovoltaic Systems: Integrating Metaheuristic and Analytical Algorithms for Optimal Performance Under Partial Shading by Alpaslan Demirci, Idriss Dagal, Said Mirza Tercan, Hasan Gundogdu, Musa Terkes, Umit Cali

“…The results demonstrate that the improved ANN-based MPPT algorithm consistently outperforms existing MPPT techniques, including the Perturb and Observe (P&O) and Grey Wolf Optimization (GWO), Harris Hawks Optimization (HHO), and Particle Swarm Optimization (PSO) methods. …”
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