Risultati della ricerca - Distribution evolution algorithm

Location-Informed Interference Suppression Precoding Methods for Distributed Massive MIMO Systems di Vanspranghels, Emiel, Oishi, Raquel Marina Noguera, Minucci, Franco, Pollin, Sofie

Sommario: “...The evolution of mobile networks towards user-centric cell-free distributed Massive MIMO...”
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GULP II: Hierarchical Distribution and Evolution of Young Stellar Structures in NGC 4449 di Meena, Beena, Sabbi, Elena, Zeidler, Peter, Elmegreen, Bruce G., Eldridge, Jan J., Bajaj, Varun, Gennaro, Mario, Pasquali, Anna, Elmegreen, Debra M., Klessen, Ralf S., Smith, Linda J., Bianchi, Luciana, Wofford, Aida, Facchini, Pietro, Gallagher III, John S., Calzetti, Daniela, Grebel, Eva K., Adamo, Angela

Sommario: “... -- a density-based clustering algorithm -- and trace their evolution over time. While comparing...”
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Data-Driven Stochastic Distribution System Hardening Based on Bayesian Online Learning di Shi, Wenlong, Li, Hongyi, Wang, Zhaoyu

Sommario: “... the probabilistic evolution of outage scenarios under various hardening decisions. Based on the DNN predictions...”
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Quantum Walks-Based Adaptive Distribution Generation with Efficient CUDA-Q Acceleration di Chang, Yen-Jui, Wang, Wei-Ting, Liu, Chen-Yu, Wang, Yun-Yuan, Chang, Ching-Ray

Sommario: “...We present a novel Adaptive Distribution Generator that leverages a quantum walks-based approach...”
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Concentration Within Distribution: Unmasking Bitcoin's Structural Centralization Through Network Science di Nonaka, Myriam, Marín-Rodríguez, F. Javier, Jiricny, Alexander, Romance, Miguel, Criado, Regino, Iglesias-Pérez, Sergio, Partida, Alberto

Sommario: “..., which allows us to explore its mesoscopic properties and trace its temporal evolution. In particular, we...”
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A Guide to Tracking Phylogenies in Parallel and Distributed Agent-based Evolution Models di Moreno, Matthew Andres, Ranjan, Anika, Dolson, Emily, Zaman, Luis

Sommario: “...Computer simulations are an important tool for studying the mechanics of biological evolution...”
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Polystyrene Particle Size Distribution with the Use of Modified Time Increment Monte Carlo Model di Soheyl Khajehpour‐Tadavani, Hossein Abedini, Mehdi Nekoomanesh‐Haghighi, Amanda Lemette Teixeira Brandão

Sommario: “... for predicting the dynamic evolution of monomer Droplet Size Distribution (DSD) and polymer Particle Size...”
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Non-iterative Optimization Algorithm for Active Distribution Grids Considering Uncertainty of Feeder Parameters di Wu, J., Liu, M., Lu, W., Xie, K., Xie, M.

Sommario: “... novel non-iterative algorithm to track the optimal solutions. Different from existing methods...”
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Regional Deformation Anomaly Assessment of Arch Dam Considering the Extreme Value Distribution of Deviations di Xudong Chen, Qinghe Lu, Liuyang Li, Hongdi Guo, Yu Deng, Jinjun Guo, Chongshi Gu, Xing Liu

Sommario: “...Regional Deformation Anomaly Assessment of Arch Dam Considering the Extreme Value Distribution...”
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Prob-GParareal: A Probabilistic Numerical Parallel-in-Time Solver for Differential Equations di Gattiglio, Guglielmo, Grigoryeva, Lyudmila, Tamborrino, Massimiliano

Sommario: “...We introduce Prob-GParareal, a probabilistic extension of the GParareal algorithm designed...”
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Charting the Intelligence Frontiers – Edge AI Systems Nexus

Sommario: “... the complexities of advanced algorithms and the design of novel edge AI hardware accelerators to the architecture...”
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Simulating Evolvability as a Learning Algorithm: Empirical Investigations on Distribution Sensitivity, Robustness, and Constraint Tradeoffs di Fidalgo, Nicholas, Ye, Puyuan

Sommario: “...The theory of evolvability, introduced by Valiant (2009), formalizes evolution as a constrained...”
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Optimizing Server Load Distribution in Multimedia IoT Environments through LSTM-Based Predictive Algorithms di Imanpour, Somaye, Montazerolghaem, Ahmadreza, Afshari, Saeed

Sommario: “...The Internet of Multimedia Things (IoMT) represents a significant advancement in the evolution...”
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Distributional Soft Actor-Critic with Harmonic Gradient for Safe and Efficient Autonomous Driving in Multi-lane Scenarios di Zhang, Feihong, Zhan, Guojian, Shuai, Bin, Zhang, Tianyi, Duan, Jingliang, Li, Shengbo Eben

Sommario: “...Reinforcement learning (RL), known for its self-evolution capability, offers a promising approach...”
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Understanding Challenges of Optimization‐Based Distribution of Relaxation Times of Electrochemical Impedance Spectroscopy for Commercial Fuel Cell Stack di Wenmiao Chen, Guoqing Liu, Fuqiang Xi, Yangyang Shen, Xiaohui Liu, Yuhang Hu, Siwu Yi, Yuehua Li

Sommario: “...Understanding Challenges of Optimization‐Based Distribution of Relaxation Times of Electrochemical...”
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Federated Digital Twin Construction via Distributed Sensing: A Game-Theoretic Online Optimization with Overlapping Coalitions di Chen, Ruoyang, Yi, Changyan, Zhou, Fuhui, Kang, Jiawen, Wu, Yuan, Niyato, Dusit

Sommario: “.... Considering time-varying DT evolutions and heterogeneities among partial-DTs, we formulate an online problem...”
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A Signal-Theoretic Model of Prime Number Distribution: Harmonic Mechanics in a Curvature-Limited Projection Space di kulik, dean

Sommario: “...<p> </p> <h1>A Signal-Theoretic Model of Prime Number Distribution: Harmonic...”
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Enhancing Accuracy and Efficiency in Calibration of Drinking Water Distribution Networks Through Evolutionary Artificial Neural Networks and Expert Systems di Gomez, Cristian, Solon, Kimberly, Haest, Pieter-Jan, Morley, Mark, Nopens, Ingmar, Torfs, Elena

Sommario: “...-NEAT). The proposed methodology leverages the power of Expert Systems (ES) and genetic algorithms...”
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Cost‐Effective and Low‐Carbon Emission Deployment of PV‐DG Integration in Distribution Networks Using Self‐Adaptive Bonobo Optimizer di Mohammed H. Alqahtani, Ahmed R. Ginidi, Ali S. Aljumah, Abdullah M. Shaheen

Sommario: “...Cost‐Effective and Low‐Carbon Emission Deployment of PV‐DG Integration in Distribution Networks...”
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Osilosimulator™ – High-Resolution Temporal Stability and Drift Prediction Engine Deterministic Analysis Platform for GRM™ Structural Fields di Piskač, Josef

Sommario: “... algorithms inside controlled envelopes</p> <p> </p> <p>conduct reproducible...”
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