Decision-making method for residual support force of hydraulic supports during pressurized moving under fragmented roof conditions in ultra-thin coal seams by ZHANG Chuanwei, ZHANG Gangqiang, LU Zhengxiong, LI Linyue, HE Zhengwei, GONG Lingxiao, HUANG Junfeng

“…To address this challenge, this study proposed a novel decision-making method based on a Deep Hybrid Kernel Extreme Learning Machine (DHKELM) optimized by an Improved Dung Beetle Optimization (IDBO) algorithm. …”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…Specifically, the RF algorithm achieved an accuracy of 0.9690, while the SVM algorithm attained an accuracy of 0.9587 in State 1, making them the most effective models in this setting. …”
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An optimization-inspired intrusion detection model for software-defined networking by Hui Xu, Longtan Bai, Wei Huang

“…The experimental results show that the ESWO-IDM achieves the best performance in all the metrics in both binary classification and multiclassification and has the most prominent effect on the detection of normal, denial of service (DoS), distributed DoS, and Brute Force Attack types, which effectively improves SDN intrusion detection from the viewpoint of optimization.…”
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LI-YOLO: An Object Detection Algorithm for UAV Aerial Images in Low-Illumination Scenes by Songwen Liu, Hao He, Zhichao Zhang, Yatong Zhou

“…Compared with other current algorithms, LI-YOLO improves the mAP 50 by 3.1% on the DroneVehicle dataset and 6.9% on the LLVIP dataset. …”
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Evaluation of Traditional and Data-Driven Algorithms for Energy Disaggregation Under Sampling and Filtering Conditions by Carlos Rodriguez-Navarro, Francisco Portillo, Isabel Robalo, Alfredo Alcayde

“…The selection of the optimal NILM algorithm for real-world applications must consider a balance between desired accuracy, load types, electrical signal characteristics, and crucially, the limitations of available computational resources.…”
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Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter by Andrew Lowy, Meisam Razaviyayn

“…To do so, we develop novel algorithmic and stability-based proof techniques, which we believe will be useful for future work in obtaining optimal excess risk. …”
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DP-YOLO: A Lightweight Real-Time Detection Algorithm for Rail Fastener Defects by Lihua Chen, Qi Sun, Ziyang Han, Fengwen Zhai

“…To enable accurate and efficient real-time detection of rail fastener defects under resource-constrained environments, we propose DP-YOLO, an advanced lightweight algorithm based on YOLOv5s with four key optimizations. …”
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Deep Reinforcement Learning for Optimal Replenishment in Stochastic Assembly Systems by Lativa Sid Ahmed Abdellahi, Zeinebou Zoubeir, Yahya Mohamed, Ahmedou Haouba, Sidi Hmetty

“…This study presents a reinforcement learning–based approach to optimize replenishment policies in the presence of uncertainty, with the objective of minimizing total costs, including inventory holding, shortage, and ordering costs. …”
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Traffic environment perception algorithm based on multi-task feature fusion and orthogonal attention by Zhengfeng LI, Mingen ZHONG, Yihong ZHANG, Kang FAN, Zhiying DENG, Jiawei TAN

“…In the realm of autonomous driving, the design and implementation of collaborative multi-task perception algorithms pose significant challenges. These challenges are primarily rooted in the need for real-time processing speeds, effective feature sharing among diverse tasks, and seamless information fusion. …”
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Dynamic Node Management for Energy Optimization in Cognitive Radio Systems by Tangsen Huang, Haibing Yin, Xiangdong Yin, Huijun Xiao

“…Compared to traditional algorithms, the dynamic grouping algorithm significantly enhances spectrum sensing performance and improves energy efficiency. …”
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A Biologically Inspired Cost-Efficient Zero-Trust Security Approach for Attacker Detection and Classification in Inter-Satellite Communication Networks by Sridhar Varadala, Hao Xu

“…The Manta Ray Foraging Optimization (MRFO) algorithm is used to minimize this cost, enabling effective classification of nodes as either trusted or malicious based on historical authentication records and real-time behavior. …”
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Two-Dimensional Beam Selection by Multiarmed Bandit Algorithm Based on a Quantum Walk by Maki Arai, Tomoki Yamagami, Takatomo Mihana, Ryoichi Horisaki, Mikio Hasegawa

“…Therefore, we formulate a systematic process for beam selection employing the MAB algorithm rooted in QW principles. We derive the optimal parameters of this method to maximize achievable channel capacity. …”
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A Cellular Automata-Based Crossover Operator for Binary Chromosome Population Genetic Algorithms by Doru Constantin, Costel Bălcău

“…After presenting the fundamental elements regarding cellular automata with specific examples for one- and two- dimensional cases, the the most widely used crossover operators in applications with genetic algorithms are described, and the crossover operator based on cellular automata is defined. …”
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Swarm intelligence for energy-efficient heating, ventilation, and air conditioning (HVAC) systems: A case study in smart buildings by Vinoth Kanna I, Raja Subramani, Maher Ali Rusho, Shubham Sharma, Ramachandran T, Abinash Mahapatro, Deepak Gupta, Jasmina Lozanovic

“…This research utilizes swarm intelligence algorithms—Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and hybrid PSO-ACO-to optimize energy efficiency and thermal comfort in smart building HVAC systems. …”
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Deep Learning-Based Feature Matching Algorithm for Multi-Beam and Side-Scan Images by Yu Fu, Xiaowen Luo, Xiaoming Qin, Hongyang Wan, Jiaxin Cui, Zepeng Huang

“…It also overcomes challenges, such as large nonlinear differences, significant geometric distortions, and high matching difficulty between the MBES and side-scan images, significantly improving the optimized image matching results. The matching error RMSE has been reduced to within six pixels, enabling the accurate matching of multi-beam and side-scan images.…”
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MACHINE LEARNING FOR CONCRETE SUSTAINABILITY IMPROVEMENT: SMART FLEET MANAGEMENT by Coralia TANASUICA (ZOTIC), Mihai Daniel ROMAN

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Enhancing Drought Forecast Accuracy Through Informer Model Optimization by Jieru Wei, Wensheng Tang, Pakorn Ditthakit, Jiandong Shang, Hengliang Guo, Bei Zhao, Gang Wu, Yang Guo

“…Aiming at the problem of drought forecasting accuracy in a short time scale, this study proposed a drought forecasting model named VMD-JAYA-Informer based on Variational Mode Decomposition (VMD) and the JAVA optimization algorithm to improve the Informer model. …”
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Predictive modeling of electrochromic performance in ammonium metatungstate solutions using machine learning algorithms by Bocheng Jiang, Honglong Ning, Muyun Li, Rihui Yao, Chenxiao Guo, Yucheng Huang, Zijie Guo, Dongxiang Luo, Dong Yuan, Junbiao Peng

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Dynamic strategy for adaptive block size optimization in blockchain technology by Shafique Ahmed Awan, Muazzam Ali Khan Khattak, Anwar Ali Sathio, Haleem Farman, Sumaira Memon, Moustafa M. Nasralla, Ahmed Sedik

“…This study proposes a dynamic block size optimization framework for private blockchain networks using hybrid heuristic algorithms—Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO)—integrated with Merkle trees and Directed Acyclic Graphs (DAGs). …”
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Enhancing adaptive beamforming by enhanced MUSIC algorithm for urban environments in O-RAN architecture by Mustafa Mayyahi, Jordi Mongay Batalla, Constandinos X. Mavromoustakis

“…This enhancement reduces the latency associated with beamforming adjustments, improves AoA accuracy, and optimizes beam direction preemptively, thereby improving network efficiency and user connectivity. …”
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