Iterative Inversion of Normal and Lateral Resistivity Logs in Thin-Bedded Rock Formations of the Polish Carpathians by Michał Wilkosz

“…The proposed iterative inversion procedure combines a finite element method forward modeling procedure with a particle swarm optimization algorithm to generate high-resolution models of the rock formation. …”
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Decentralized Nonstationary Fuzzy Neural Network with Meta-Learning-Net by Zhen Zhang, Meiling Yu, Hui Jia

“…To address this limitation, we propose a Decentralized NFNN (DNFNN) that overcomes the obstacles in the backward update process and enhances the efficiency of large-scale optimization. Additionally, we demonstrate improved computational efficiency and establish the linear convergence of the proposed decentralized algorithm. …”
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BAHGRF3: Human gait recognition in the indoor environment using deep learning features fusion assisted framework and posterior probability moth flame optimisation by Muhammad Abrar Ahmad Khan, Muhammad Attique Khan, Ateeq Ur Rehman, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Deepak Gupta, Saima Ahmed Rahin, Yudong Zhang

“…Results demonstrate comparable improvement in accuracy and significantly minimize the computational time with recent state‐of‐the‐art techniques.…”
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Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network by Yu Cai, Yefeng Yang, Tao Huang, Boyang Li

“…Then, the proximal policy optimization algorithm with a dual‐critic structure is proposed to address the overestimation issue and accelerate the convergence speed of RL controllers. …”
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An Overview of Deep Neural Networks for Few-Shot Learning by Juan Zhao, Lili Kong, Jiancheng Lv

“…We categorize FSL methods into three types based on strategies to increase labeled samples or reduce hypothesis space: data augmentation, model-based methods, and algorithm-optimized approaches. Using this taxonomy, we review various methods and evaluate their strengths and weaknesses. …”
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Artificial liver classifier: a new alternative to conventional machine learning models by Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid

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Improving with Hybrid Feature Selection in Software Defect Prediction by Muhammad Yoga Adha Pratama, Rudy Herteno, Mohammad Reza Faisal, Radityo Adi Nugroho, Friska Abadi

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Transmission and Generation Expansion Planning Considering Virtual Power Lines/Plants, Distributed Energy Injection and Demand Response Flexibility from TSO-DSO Interface by Flávio Arthur Leal Ferreira, Clodomiro Unsihuay-Vila, Rafael A. Núñez-Rodríguez

“…The column and constraint generation algorithm and duality-free decomposition method are adopted. …”
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Model for evaluation of technical and economic indicators of offshore wind farms by D. Y. Davydov, S. G. Obukhov

“…Evaluation of the computational speed showed a sufficiently high efficiency of the algorithm, which allows the model to be applied to optimize large offshore wind farms.…”
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Optional and mandatory assignment strategies for dynamic vehicle routing with time windows by Mustafa Demirbilek

“…In MPA, customer requests can be rejected if future requests are expected to be more advantageous, whereas MPM mandates accepting requests provided vehicle capacity is sufficient. After optimizing the methods through sensitivity analyses, we evaluated their performance against Clarke and Wright's Savings Algorithm (CW) across various real-world-inspired scenarios, including different time window lengths, interarrival times, and region types. …”
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Dynamic control of a 10 MW solar-autothermal hybrid biomass gasifier for round-the-clock processing with stable syngas production by Axel Curcio, Sylvain Rodat, Valéry Vuillerme, Stéphane Abanades

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Improving distributed systems failure prediction via multi-objective feature selection and deep forest by Zhidan Yuan, Yikai Zhang, Yingqi Yu, Taizhi Lv, Tao Huang

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Assessment model of ozone pollution based on SHAP-IPSO-CNN and its application by Xiaolei Zhou, Xingyue Wang, Ruifeng Guo

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Machine Learning and Deep Learning for Loan Prediction in Banking: Exploring Ensemble Methods and Data Balancing by Eslam Hussein Sayed, Amerah Alabrah, Kamel Hussein Rahouma, Muhammad Zohaib, Rasha M. Badry

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Dynamic Adaptive Parametric Social Network Analysis Using Reinforcement Learning: A Case Study in Topic-Aware Influence Maximization by Mohammad Hossein Ahmadikia, Mehdy Roayaei

“…Current network analysis algorithms often rely on search methods or centrality measures but face challenges such as 1) The solution space is large, resulting in high computational complexity. 2) Algorithms may be instance-dependent, relying considerably on network structure and characteristics, which may result in varying performance across different networks. 3) Most existing centrality measures are inherently static, which fail to capture the dynamic nature inherent in network analysis problems. …”
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Mixed Balanced Truncation for Reducing the Complexity of Large-Scale Electrical and Electronic System Simulations by Huy-Du Dao, Thanh-Tung Nguyen, Ngoc-Kien Vu, Van-Ta Hoang, Hong-Quang Nguyen

“…This study focuses on Model Order Reduction (MOR) to optimize such systems' simulation and analysis capabilities in the context of increasingly complex electrical and electronic systems, coupled with computational and processing resource limitations. …”
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Automated Recognition of Abnormalities in Gastrointestinal Endoscopic Images – Evaluation of an AI Tool for Identifying Polyps and Other Irregularities by Weronika Jarych, Elżbieta Tokarczyk, Patryk Iglewski, Daria Ziemińska, Karina Motolko, Rafał Burczyk, Konrad Duszyński, Michał Kociński, Jan Reinald Wendt

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Three Dimensional Image Reconstruction of Electrical Capacitance Tomography Based on Improved ALEXNET Convolutional Neural Network by LI Yan, WANG Lu, LI Jiaqi

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Highly-Efficient Hardware Architecture for ML-KEM PQC Standard by Haesung Jung, Quang Dang Truong, Hanho Lee

“…The advent of quantum computers, with their immense computational potential, poses significant threats to traditional cryptographic systems. …”
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A hybrid CFD and machine learning study of energy performance of photovoltaic systems with a porous collector: Model development and validation by Yinling Wang, Lei Yu, Mazhar Ali, Imran Ali Khan, Tahir Maqsood, Haining Gao, Qi Wang, Xiaolei Guo

“…A systematic preprocessing pipeline was developed to enhance model performance, including outlier detection and feature normalization. Hyperparameter optimization process in this study uses the Water Cycle Algorithm (WCA), a metaheuristic method inspired by natural processes. …”
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