A Novel Artificial Bee Colony Approach of Live Virtual Machine Migration Policy Using Bayes Theorem by Gaochao Xu, Yan Ding, Jia Zhao, Liang Hu, Xiaodong Fu

“…As a result, the whole approach achieves a longer-term efficient optimization for power saving. …”
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Energy management in a microgrid equipped with an electric vehicle based on the internet of things considering responsive load by Mohamad Mahdi Erfani Majd, Reza Davarzani, Mahmoud Samiei Moghaddam, Ali Asghar Shojaei, Mojtaba Vahedi

“…A novel Energy-Trading Management Algorithm (ETMA), based on the Meerkat Optimization Algorithm (MOA), is proposed to tackle the complexities of this system. …”
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Subspace-based local compilation of variational quantum circuits for large-scale quantum many-body simulation by Shota Kanasugi, Yuichiro Hidaka, Yuya O. Nakagawa, Shoichiro Tsutsui, Norifumi Matsumoto, Kazunori Maruyama, Hirotaka Oshima, Shintaro Sato

“…Here, we propose a hybrid quantum-classical algorithm, called local subspace variational quantum compilation (LSVQC), for compiling the time-evolution operator of quantum many-body systems. …”
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Intelligent building design based on green and low-carbon concept by Qian Lv

“…Guided by the concept of green and low-carbon, intelligent building design emphasizes the full utilization of renewable energy while utilizing advanced algorithms to optimize energy scheduling in intelligent buildings, achieving green, low-carbon, energy-saving, and emission-reduction goals. …”
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Design and Implementation of Hybrid GA-PSO-Based Harmonic Mitigation Technique for Modified Packed U-Cell Inverters by Hasan Iqbal, Arif Sarwat

“…By utilizing the multi-objective optimization method, the approach minimizes THD while keeping voltage and efficiency constraints. …”
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Stratified Object-Oriented Image Classification Based on Remote Sensing Image Scene Division by Wen Zhou, Dongping Ming, Lu Xu, Hanqing Bao, Min Wang

“…This method firstly uses middle semantic which can reflect an image’s visual complexity to classify the remote sensing image into different scenes, and then within each scene, an improved grid search algorithm is employed to optimize the segmentation result of each scene, so that the optimal scale can be utmostly adopted for each scene. …”
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FPGA Acceleration With Hessian-Based Comprehensive Intra-Layer Mixed-Precision Quantization for Transformer Models by Woohong Byun, Jongseok Woo, Saibal Mukhopadhyay

“…Coupled with the proposed algorithm and dataflow optimization, it enables on-chip storage of all necessary parameters, minimizing off-chip memory access. …”
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Comparative analysis of machine learning models for malaria detection using validated synthetic data: a cost-sensitive approach with clinical domain knowledge integration by Gudi V. Chandra Sekhar, Chekol Alemu

“…While synthetic data enables controlled algorithm comparison, real-world clinical validation remains essential before deployment.…”
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Self-Adjusting Look-Ahead Distance of Precision Path Tracking for High-Clearance Sprayers in Field Navigation by Xu Wang, Bo Zhang, Xintong Du, Huailin Chen, Tianwen Zhu, Chundu Wu

“…The tracking accuracy has been improved and the applicability of the algorithm for rapid deployment has been enhanced.…”
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Overheating Defect Detection of Composite Insulator Based on Mask R-CNN by Yi GAO, Lianfang TIAN, Qiliang DU

“…Firstly, in order to improve the accuracy of segmentation, the Mask R-CNN network is improved according to the idea of Cascade R-CNN, and the data augmentation and transfer learning methods are used for model training to improve the network performance. …”
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Explainable AI-Based Ensemble Clustering for Load Profiling and Demand Response by Elissaios Sarmas, Afroditi Fragkiadaki, Vangelis Marinakis

“…Notably, while ensemble clustering often ranked among the top performers, it did not consistently surpass all individual algorithms, indicating its potential for further optimization. …”
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Adaptive robust self‐scheduling for a wind‐based GenCo equipped with power‐to‐gas system and gas turbine to participate in electricity and natural gas markets by Mojtaba Fereydani, Mohammad Amin Latify

“…A column & constraint generation (C&CG) algorithm is used to solve the model. Numerical results demonstrate the model’s effectiveness in various case studies, showing that the GenCo can manage wind uncertainties, benefit from arbitrage opportunities in electricity and gas markets, and improve economic outcomes. …”
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Power-Yeoh: A Yeoh-Type Hyperelastic Model with Invariant I₂ for Rubber-like Materials by Subraya Krishna Bhat, Keerthan A.

“…Also, the interesting phenomenon of thin balloon expansion is investigated by applying the model to relevant experimental data on elastomeric balloons available in the literature. A genetic algorithm-based least squares optimization routine is carried out to determine the material constants while applying the reported experimental data. …”
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Deep Reinforcement Learning-Based Active Disturbance Rejection Control for Trajectory Tracking of Autonomous Ground Electric Vehicles by Xianjian Jin, Huaizhen Lv, Yinchen Tao, Jianning Lu, Jianbo Lv, Nonsly Valerienne Opinat Ikiela

“…The framework integrates active disturbance rejection control (ADRC) for real-time disturbance estimation and compensation with a deep deterministic policy gradient (DDPG)-based deep reinforcement learning (DRL) algorithm for dynamic optimization of controller parameters to improve tracking accuracy and robustness. …”
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Linear B-cell epitope prediction for SARS and COVID-19 vaccine design: Integrating balanced ensemble learning models and resampling strategies by Fatih Gurcan

“…The rebalanced datasets were then used in model building with ensemble classifiers employing Boosting, Bagging, and Balancing strategies. Hyperparameter optimization for the classifiers was conducted using GridSearchCV, while feature selection was performed with the recursive feature elimination (RFE) algorithm. …”
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Incremental learning with SVM for multimodal classification of prostatic adenocarcinoma. by José Fernando García Molina, Lei Zheng, Metin Sertdemir, Dietmar J Dinter, Stefan Schönberg, Matthias Rädle

“…We propose a pattern recognition system with an incremental learning ensemble algorithm using support vector machines (SVM) tackling this problem employing multimodal MR images and a texture-based information strategy. …”
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Multi-Underwater Target Interception Strategy Based on Deep Reinforcement Learning by Wenhao GAN, Yunfei PENG, Lei QIAO

“…Next, the multi-agent proximal policy optimization algorithm was used to construct a scalable state and action space and design a compound reward function, enhancing interception efficiency and cooperation of AUVs. …”
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3D evolutionarily designed metamaterials for scattering maximization by Dmitry Dobrykh, Konstantin Grotov, Anna Mikhailovskaya, Dmytro Vovchuk, Vladyslav Tkach, Mykola Khobzei, Anton Kharchevskii, Aviel Glam, Pavel Ginzburg

“…The resonance cascading is engineered with the aid of multi-objective optimization, implemented on top of a genetic algorithm, operating in a large search space, encompassing over 100 independent variables. …”
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Eecs-fl: energy-efficient client selection for federated learning in AIoT by Yiyang Zhang, Yiming Luo, Tao Yang, Xiaofeng Wu, Bo Hu

“…We formulate the client selection problem as a multi-dimensional knapsack problem (MKP) and solve it using dynamic programming to maximize energy efficiency while maintaining fast convergence. Experimental results show that incorporating WPT leads to a reduction in unit energy consumption by over 24.54%; while, the proposed algorithm achieves a reduction of over 15.31% compared to random selection. …”
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A comprehensive techno-economic analysis for a PHEV-integrated microgrid system involving wind uncertainty and diverse demand side management policies by Bishwajit Dey, Laishram Khumanleima Chanu, Gulshan Sharma, Pitshou N. Bokoro

“…The research investigation employed the Differential Evolution (DE) algorithm as an optimization technique. Numerical results show that the total operating cost (TOC) of the MG system reduced from $25,575 during the base load model to $24,521 when the proposed hybrid DSM was implemented. …”
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