Výsledky vyhledávání - "predictive power"

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A Fast Dynamic Internal Predictive Power Scheduling Approach for Power Management in Microgrids

Autor: Maya, Neethu, Poolla, Bala Kameshwar, Srinivasan, Seshadhri, Sundararajan, Narasimman, Sundaram, Suresh

This paper presents a Dynamic Internal Predictive Power Scheduling (DIPPS) approach for optimizing power management in microgrids, particularly focusingon external power exchanges among diverse prosumers. DIPPS utilizes a dynamic objective function w

Externí odkaz: http://arxiv.org/abs/2409.16643

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Predictive power-sharing scaling law in double-null L-mode plasmas

Autor: Lim, K., Ricci, P., Stenger, L., De Lucca, B., Durr-Legoupil-Nicoud, G., Février, O., Theiler, C., Verhaegh, K.

The physical mechanisms regulating the power sharing at the outer targets of L-mode double-null (DN) configurations are investigated using nonlinear, flux-driven, three-dimensional two-fluid simulations. Scans of parameters that regulate the turbulen

Externí odkaz: http://arxiv.org/abs/2406.19684

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Evolving reservoir computers reveals bidirectional coupling between predictive power and emergent dynamics

Autor: Tolle, Hanna M., Luppi, Andrea I, Seth, Anil K., Mediano, Pedro A. M.

Biological neural networks can perform complex computations to predict their environment, far above the limited predictive capabilities of individual neurons. While conventional approaches to understanding these computations often focus on isolating

Externí odkaz: http://arxiv.org/abs/2406.19201

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Kolmogorov-Arnold Networks for Time Series: Bridging Predictive Power and Interpretability

Autor: Xu, Kunpeng, Chen, Lifei, Wang, Shengrui

Kolmogorov-Arnold Networks (KAN) is a groundbreaking model recently proposed by the MIT team, representing a revolutionary approach with the potential to be a game-changer in the field. This innovative concept has rapidly garnered worldwide interest

Externí odkaz: http://arxiv.org/abs/2406.02496

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Intensity Normalization Techniques and Their Effect on the Robustness and Predictive Power of Breast MRI Radiomics

Autor: Schwarzhans, Florian, George, Geevarghese, Sanchez, Lorena Escudero, Zaric, Olgica, Abraham, Jean E, Woitek, Ramona, Hatamikia, Sepideh

Radiomics analysis has emerged as a promising approach for extracting quantitative features from medical images to aid in cancer diagnosis and treatment. However, radiomics research currently lacks standardization, and radiomics features can be highl

Externí odkaz: http://arxiv.org/abs/2406.01736

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Predictive power of the Berezinskii-Kosterlitz-Thouless theory based on Renormalization Group throughout the BCS-BEC crossover in 2D superconductors

Autor: Midei, Giovanni, Furutani, Koichiro, Salasnich, Luca, Perali, Andrea

Recent experiments on 2D superconductors allow the characterization of the critical temperature and of the phase diagram across the BCS-BEC crossover as a function of density. We obtain from these experiments the microscopic parameters of the superco

Externí odkaz: http://arxiv.org/abs/2403.03025

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Akademický článek

Predictive power control strategy without grid voltage sensors of the Vienna rectifier

Autor: Tao Yang, Lan Chen, Yiru Miao

Publikováno v: IET Power Electronics, Vol 17, Iss 11, Pp 1411-1421 (2024)

Abstract This paper proposes a predictive power control strategy for the three‐phase, six‐switch Vienna rectifier without grid voltage sensors to reduce the hardware cost and complexity of a high‐power PWM rectifier system. Firstly, an algorith

Externí odkaz: https://doaj.org/article/3b6e5d0e1a7442d487fd96b174fdbb9d