A Cooperative Generation Expansion Planning of Microgrids to Improve the Resiliency of Active Distribution Networks by Mohammad Hossein Atazadegan, Esmaeel Rokrok, Meysam Doostizadeh

“…In this case, the multi objective optimization problem, including the objective functions of total cost and environmental pollution, has been solved using fuzzy decision-making and multi-objective improved golden ratio optimization algorithm based on the Pareto front.…”
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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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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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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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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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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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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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RRMSE-enhanced weighted voting regressor for improved ensemble regression. by Shikun Chen, Wenlong Zheng

“…This uniform weighting approach doesn't consider that some models may perform better than others on different datasets, leaving room for improvement in optimizing ensemble performance. To overcome this limitation, we propose the RRMSE (Relative Root Mean Square Error) Voting Regressor, a new ensemble regression technique that assigns weights to each base model based on their relative error rates. …”
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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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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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MACHINE LEARNING FOR CONCRETE SUSTAINABILITY IMPROVEMENT: SMART FLEET MANAGEMENT by Coralia TANASUICA (ZOTIC), Mihai Daniel ROMAN

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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

“…In another study, Akbari and Yazdanian (2023) applied machine learning algorithms to determine optimal thresholds for operational loss severity data, classifying the data and estimating the capital required to cover operational risk by integrating severity and frequency distribution functions with Monte Carlo simulation. …”
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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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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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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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Highly Precise Time Compensation Algorithm for Synchronous Communication System Based on Least Squares by Jin Su, Changshui Li, Qingbo Liu, Sheng Zhao, Xiangyu Wang

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Application of deep learning algorithm for judicious use of anti-VEGF in diabetic macular edema by Anwesa Mondal, Apurba Nandi, Subhasish Pramanik, Lakshmi Kanta Mondal

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Optimization of transportation efficiency through fuzzy logic and LINGO software by Zahoor Ahmad Ganie, Zahid Gulzar Khaki, Tanveer Ahmad Tarray, Gazala Salam, Eid Sadun Alotaibi

“…This study significantly contributes to the development of optimization algorithms and transportation systems with a solid basis for accurate, privacy-preserving data collection and efficient decision-making.…”
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