Using the clustering method to find the final environmental parameters coefficients in road construction projects by Eshagh Rasouli Sarabi, Ramin Vafaei Poursorkhabi, Mehdi Ravanshadnia

“…In the first phase, the Genetic Optimization Algorithm was implemented to determine convenient coefficients for the relevant parameters. …”
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Recovery and Characterization of Tissue Properties from Magnetic Resonance Fingerprinting with Exchange by Naren Nallapareddy, Soumya Ray

“…Our results show that Simplicial Homology Global Optimization (SHGO), a global optimization algorithm, and Limited-memory Bryoden–Fletcher–Goldfarb–Shanno algorithm with Bounds (L-BFGS-B), a local optimization algorithm, performed comparably with direct matching in two-tissue property MRF at an SNR of 5. …”
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Optimal Power Flow for High Spatial and Temporal Resolution Power Systems with High Renewable Energy Penetration Using Multi-Agent Deep Reinforcement Learning by Liangcai Zhou, Long Huo, Linlin Liu, Hao Xu, Rui Chen, Xin Chen

“…A heterogeneous multi-agent proximal policy optimization (H-MAPPO) DRL algorithm is introduced for multi-area power systems. …”
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Strategic Deployment of a Single Mobile Weather Radar for the Enhancement of Meteorological Observation: A Coverage-Based Location Problem by Bikram Parajuli, Xin Feng

“…The proposed location problem is solved optimally using the geometric branch-and-bound algorithm and heuristically using swarm-based optimization algorithms. …”
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A Cooperative GNSS Vector-DLL (CoVDLL) Method for Multiple UAVs Positioning by Chuntao Li, Xinru Wang, Changhui Jiang, Zikang Su, Shoubin Chen, Yuwei Chen

“…To optimize navigation solution estimation in the CoVDLL, a Factor Graph Optimization (FGO) algorithm is employed to realize the navigation solution’s optimal estimation. …”
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Enhancing Privacy in IoT Networks: A Comparative Analysis of Classification and Defense Methods by Ahmet Emre Ergun, Ozgu Can, Murat Kantarcioglu

“…As a defense mechanism, DP is applied using the Fourier Perturbation Algorithm (FPA) to optimize padding strategies while maintaining network efficiency. …”
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Potential of random forest machine learning algorithm for geological mapping using PALSAR and Sentinel-2A remote sensing data: A case study of Tsagaan-uul area, southern Mongolia by Munkhsuren Badrakh, Narantsetseg Tserendash, Erdenejargal Choindonjamts, Gáspár Albert

“…Geological mapping in remote and geologically complex regions can be substantially improved by integrating remote sensing data with machine learning algorithms. This study evaluates the effectiveness of the Random Forest algorithm for geological mapping in the Tsagaan-uul area of the Khatanbulag ancient massif, Mongolia, a region characterized by limited accessibility and sparse field data. …”
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A carbon aware ant colony system for the sustainable generalized traveling salesman problem by Marina Lin, Laura P. Schaposnik

“…In an era where sustainability is becoming increasingly crucial, we introduce a novel Carbon-Aware Ant Colony System (CAACS) Algorithm that addresses the Generalized Traveling Salesman Problem while minimizing carbon emissions. …”
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Photovoltaic Hosting Capacity Assessment of Distribution Networks Considering Source–Load Uncertainty by Chao Chen, Weifeng Peng, Cheng Xie, Shufeng Dong, Yibo Hua

“…The model considers system constraints and employs the sparrow search algorithm (SSA) to optimize the maximum PV hosting capacity. …”
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Vertex Coloring and Eulerian and Hamiltonian Paths of Delaunay Graphs Associated with Sensor Networks by Manuel Ceballos, María Millán

“…Sensor networks represent distributed systems of interconnected devices that collect and transmit data, while graph theory provides a robust framework for modeling and analyzing complex networks. …”
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A Hybrid Evolutionary Fuzzy Ensemble Approach for Accurate Software Defect Prediction by Raghunath Dey, Jayashree Piri, Biswaranjan Acharya, Pragyan Paramita Das, Vassilis C. Gerogiannis, Andreas Kanavos

“…To address this, effective feature selection is essential but remains an NP-hard challenge best tackled with heuristic algorithms. This study introduces a binary, multi-objective starfish optimizer for optimal feature selection, balancing feature reduction and classification performance. …”
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Achieving high precision and productivity in laser machining of Ti6Al4V alloy: A comprehensive study using a n-predictor polynomial regression model and PSO algorithm by Avinash Chetry, Sandesh Sanjeev Phalke, Arup Nandy

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Classification of Paddy Rice Planting Area Through Feature Selection Method Using Sentinel-1/2 Time Series Images by Shiyu Zhang, Pengao Li, Yong Xie, Wen Shao, Xueru Tian

“…Therefore, this study took Liyang City as the study area, reconstructed Sentinel-2 cloud-free time series optical images, and extracted spectral features, vegetation indexes, and other features, in combination with the polarization features of the Sentinel-1 time series radar images. The optimal feature subset was selected through the feature selection method, and machine learning algorithms were optimized for paddy rice planting area classification. …”
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NoiseAugmentNet-HHO: Enhancing Histopathological Image Classification Through Noise Augmentation by Prem Purusottam Jena, Debahuti Mishra, Kaberi Das, Sashikala Mishra

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SIDDA: SInkhorn Dynamic Domain Adaptation for image classification with equivariant neural networks by Sneh Pandya, Purvik Patel, Brian D Nord, Mike Walmsley, Aleksandra Ćiprijanović

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Early stage prediction of bone regeneration using FEA and cell differentiation algorithms with 3D-printed PLA and PCL scaffolds: modeling and application to dorsal double-plating i... by Hsuan Chih Liu, Ya-Han Chan, Shao-Fu Huang, Wei-Che Tsai, Yen Cheng, Chun-Li Lin

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Privacy-Preserving Federated Learning for Space–Air–Ground Integrated Networks: A Bi-Level Reinforcement Learning and Adaptive Transfer Learning Optimization Framework by Ling Li, Lidong Zhu, Weibang Li

“…Specifically, (1) an adaptive knowledge-sharing mechanism based on transfer learning is designed to balance device heterogeneity and data distribution divergence through dynamic weighting factors; (2) a bi-level reinforcement learning device selection strategy is proposed, combining meta-learning and hierarchical attention mechanisms to optimize global–local decision-making and enhance model convergence efficiency; (3) dynamic privacy budget allocation and robust aggregation algorithms are introduced to reduce communication overhead while ensuring privacy. …”
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Anatomical Parameter-driven Volumetric Modulated Arc Therapy Optimization in Left-sided Breast Cancer: A Machine Learning Framework for Lung Dose Prediction by Mukesh Kumar Zope, Deepali Patil, Rishi Raj, Seema Devi, Richa Madhawi

“…In addition, we established predictive models for lung doses utilizing the Least Absolute Shrinkage and Selection Operator, ridge, and linear regression algorithms while also evaluating dosimetric parameters for both the PTV and the organs at risk (OARs). …”
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Multi-Project Scheduling with Uncertainty and Resource Flexibility: A Narrative Review and Exploration of Future Landscapes by Marzieh Aghileh, Anabela Tereso, Filipe Alvelos, Maria Odete Monteiro Lopes

“…It categorizes solution approaches, from exact algorithms to heuristic and metaheuristic methods, while reviewing the primary instance sets and benchmarks used in the field. …”
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Intelligent Wireless Power Scheduling for Lunar Multienergy Systems: Deep Reinforcement Learning for Real-Time Adaptive Beam Steering and Vehicle-to-Grid Energy Optimization by Thomas Tongxin Li, Shuangqi Li, Cynthia Xin Ding, Zhaoyao Bao, Mohannad Alhazmi

“…The results validate the feasibility of DRL–based WPT control, paving the way for scalable, resilient, and self-optimizing wireless power grids on the Moon. Future work will explore the integration of hybrid energy storage models, quantum-inspired optimization for real-time decision-making, and predictive beamforming algorithms to further enhance the reliability and efficiency of lunar energy networks.…”
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