Segmentation Studies on Al‐Si‐Mg Metallographic Images Using Various Different Deep Learning Algorithms and Loss Functions by Abeyram M. Nithin, Murukessan Perumal, M. J. Davidson, M. Srinivas, C. S. P. Rao, Katika Harikrishna, Jayant Jagtap, Abhijit Bhowmik, A. Johnson Santhosh

“…Other deep learning algorithms, such as Segnet, Resnet, and FCN, were compared with the Unet approach that was suggested. …”
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Distribution Network Reconfiguration for Power Loss Reduction and Voltage Profile Improvement Using Chaotic Stochastic Fractal Search Algorithm by Tung Tran The, Dieu Vo Ngoc, Nguyen Tran Anh

“…This paper proposes a chaotic stochastic fractal search algorithm (CSFSA) method to solve the reconfiguration problem for minimizing the power loss and improving the voltage profile in distribution systems. …”
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Paradigmatic Relations of the Metalanguage of Metalinguistics by Sergey V. Lesnikov

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Comparison of diagnostic algorithms in clinically suspected viral myocarditis: Agreement between cardiovascular magnetic resonance, endomyocardial biopsy, and troponin T by Hafisyatul Zainal, Andreas Rolf, Hui Zhou, Moises Vasquez, Felicitas Escher, Till Keller, Mariuca Vasa-Nicotera, Andreas M. Zeiher, Heinz-Peter Schultheiss, Eike Nagel, Valentina O. Puntmann

“…Conclusion: In clinically suspected viral myocarditis, all diagnostic approaches reflect the pathophysiological elements of myocardial inflammation; however, the differing underlying drivers only partially overlap. The EMB and CMR diagnostic algorithms are neither interchangeable in terms of interpretation of myocardial inflammation nor in their relationship with myocardial injury.…”
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Experimentally Constrained Mechanistic and Data-Driven Models for Simulating NMDA Receptor Dynamics by Duy-Tan J. Pham, Jean-Marie C. Bouteiller

“…Determination of the kinetic model’s parameter values was performed using the particle swarm optimization algorithm. The optimized kinetic model was then used to generate a rich input–output dataset to train the look-up table synapse model and estimate its coefficients. …”
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Simulation and Optimization of Multi-Phase Terminal Trajectory for Three-Dimensional Anti-Ship Missiles Based on Hybrid MOPSO by Jiandong Sun, Shixun You, Di Hua, Zhiwei Xu, Peiyao Wang, Zihang Yang

“…To overcome these challenges, this research introduces a three-dimensional (3D) multi-stage trajectory optimization approach based on the hybrid multi-objective particle swarm optimization algorithm (MOPSO-h). A multi-stage optimization model is developed for terminal trajectory, dividing the flight process into three stages: cruising, altitude adjustment, and penetration dive. …”
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Impact of Coordinated Electric Ferry Charging on Distribution Network Using Metaheuristic Optimization by Rajib Baran Roy, Sanath Alahakoon, Piet Janse Van Rensburg

“…A dynamic model of BESS operation is optimized using a balanced hybrid metaheuristic algorithm combining GA-PSO-BFO (Genetic Algorithm-Particle Swarm Optimization-Bacterial Foraging Optimization). …”
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Outage reduction in 5G uplink cooperative NOMA using PSO-optimized relay selection and successive interference cancelation by David S. Bhatti, M. Asif Haroon, Haeung Choi, Seungmin Kim, Heung-No Lee

“…We compared the performance of particle swarm optimization (PSO) with that of the genetic algorithm (GA) and deep reinforcement learning (DRL). …”
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Accurate detection of low concentrations of microplastics in soils via short-wave infrared hyperspectral imaging by Huan Chen, Taesung Shin, Bosoon Park, Kyoung Ro, Changyoon Jeong, Hwang-Ju Jeon, Pei-Lin Tan

“…This study evaluated the effectiveness of coupling machine learning algorithms with short-wave infrared hyperspectral imaging in detecting two types of microplastics - polyamide and polyethylene - with the maximum particle sizes of 50 and 300 ​μm, respectively, across three concentration ranges (0.01–0.10, 0.10–1.0, and 1.0–12 ​%) in soils. …”
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Combined single- and dual-energy CT workflow for dose calculation in radiotherapy by Hella Sand, Jens Edmund, Ane Appelt, Patrick Wohlfahrt, Vicki Trier Taasti, Laurids Østergaard Poulsen, Jimmi Søndergaard, Martin Skovmos Nielsen

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OCT-based diagnosis of glaucoma and glaucoma stages using explainable machine learning by Md Mahmudul Hasan, Jack Phu, Henrietta Wang, Arcot Sowmya, Michael Kalloniatis, Erik Meijering

“…Leveraging SHapley Additive exPlanations (SHAP)-based global feature ranking and partial dependency analysis (PDA) estimated decision boundary cut-offs on machine learning (ML) models, a novel algorithm was developed to implement an XAI tool. …”
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An Investigation into the Rescue-Path Planning Algorithm for Multiple Mine Rescue Teams Based on FA-MDPSO and an Improved Force-Directed Layout by Qiangyu Zheng, Peijiang Ding, Zhixin Qin, Zhenguo Yan

“…Subsequently, the hyperparameters of MDPSO (Multiple Constraints Discrete Particle Swarm Optimisation) were optimised by means of four intelligent algorithms—ACO (Ant Colony Optimization), FA (Firefly Algorithm), GWO (Grey Wolf Optimizer) and WOA (Whale Optimization Algorithm). …”
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A Study on a Variable-Gain PID Control for a Pneumatic Servo System Using an Optimized PSO-Type Neural Network by Shenglin Mu, Satoru Shibata, Daisuke Baba, Rikuto Oshita

“…This study investigates the application of proportional–integral–derivative (PID) control enhanced with an optimized particle swarm optimization (OPSO)-type neural network (NN) to improve the control performance of a pneumatic servo system. …”
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An Optimized Hybrid PSO-ELM for Parkinson’s Disease Diagnosis by Gunakala Archana, Afzal Hussain Shahid

“…This paper employs three feature ranking algorithms, namely ReliefF, minimum Redundancy Maximum relevance (mRMR), and Fisher, on six publicly available PD datasets. …”
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Dynamic Foraging in Swarm Robotics: A Hybrid Approach with Modular Design and Deep Reinforcement Learning Intelligence by Ali Hammoud, Alaa Iskandar, Béla Kovács

“…This paper proposes a hybrid approach that combines intelligent algorithms and modular design to solve a foraging problem within the context of swarm robotics. …”
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A hybrid deep learning and differential evolution approach for accurate fake news detection by Shailendra Pratap Singh, Naween Kumar, Gyanendra Kumar, Ahamed Shafeeq B.M.

“…Experimental results on benchmark datasets demonstrate that the hybrid approach achieves superior accuracy, precision, recall, and F1-score compared to existing methods such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and standalone deep learning models. …”
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Intelligent Monitoring and Treatment System of Heavy Metal Contaminated Soil Based on Artificial Bee Colony Algorithm and Edge Computing Nanotechnology by Ke Hu, Dongdong Li, Xiaolei Cui, Donghua Hu, Junliang Chen, Shaopeng Zhuan, Hao Chang, Yaping Zhang, Tingting An, Juqin Zhang

“…Abstract The CGABC algorithm improves the convergence speed of the algorithm by crossing the solution generated by the neighborhood search of bees with the current global optimal solution. …”
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Data-driven prediction of critical diameter for deterministic lateral displacement devices: an integrated DPD-ML approach by Shuai Liu, Peng Zhang, Anbin Wang, Keke Tang, Shuo Chen, Chensen Lin

“…This leads to significant economic and time costs, while the complexity of instruments and algorithms further raises the barrier for DLD design and optimization. …”
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Influencing factors of cross screening rate and its intelligent prediction model by Lala ZHAO, Feng XU, Chenlong DUAN, Chenhao GUO, Wei WANG, Haishen JIANG, Jinpeng QIAO

“…Based on linear regression (LR), support vector machine (SVM), decision tree (DT) and random forest (RF) algorithms, four intelligent prediction models of cross screening rate were established. …”
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Evaluation of Support Types of Volcanic Clastic Sand and Gravels Based on Electrical Imaging Logging by ZHAO Xiaoqing, WANG Xiangyu, ZHANG Zhiguo, ZHANG Weifeng, CHEN Haifeng

“…By analyzing the oil-bearing characteristics of the core in relation to different grain-size combinations, the support type of gravel particles is determined, and the combination of the particle size spectrum and the particle size area spectrum results in an evaluation method of the support type of volcanic clastic sand conglomerate based on electrical imaging logging. …”
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