Results 21 to 30 of about 530,036 (269)

Efficient Hybrid Deep Learning Model for Battery State of Health Estimation Using Transfer Learning

Energies
Achieving accurate battery state of health (SOH) estimation is crucial, but existing methods still face many challenges in terms of data quality, computational efficiency, and cross-scenario generalization capabilities.
Jinling Ren, Misheng Cai, Dapai Shi
doaj   +1 more source

Research on Ultra-Short-Term Prediction Model of Wind Power Based on Attention Mechanism and CNN-BiGRU Combined

Frontiers in Energy Research, 2022
With the rapid development of new energy technologies and aiming at the proposal of the “DOUBLE CARBON” goal, the proportion of wind energy and other new sustainable energy power solutions in the power industry continues to increase and occupy a more ...
Yuyu Meng, Yuyu Meng, Chen Chang, Chen Chang, Jiuyuan Huo, Jiuyuan Huo, Jiuyuan Huo, Yaonan Zhang, Hamzah Murad Mohammed Al-Neshmi, Jihao Xu, Tian Xie   +10 more
doaj   +1 more source

SynthSecureNet: An Improved Deep Learning Architecture with Application to Intelligent Violence Detection

Algorithms
We present a new deep learning architecture, named SynthSecureNet, which hybridizes two popular architectures: MobileNetV2 and ResNetV2. The latter have been shown to be promising in violence detection.
Ntandoyenkosi Zungu, Peter Olukanmi, Pitshou Bokoro   +2 more
doaj   +1 more source

3D Hybrid Numerical Model of Residual Stresses: Numerical—Sensitivity to Cutting Parameters When Turning 15-5PH Stainless Steel

Journal of Manufacturing and Materials Processing, 2021
This paper investigates the residual stresses induced by a longitudinal turning operation in 15-5PH martensitic stainless steel. An experimental investigation has quantified the sensitivity of residual stresses to cutting speed, feed, tool geometry and ...
Alexandre Mondelin, Frédéric Valiorgue, Joël Rech, Michel Coret   +3 more
doaj   +1 more source

A Synergistic Framework for Coupling Crop Growth, Radiative Transfer, and Machine Learning to Estimate Wheat Crop Traits in Pakistan

Remote Sensing
The integration of the Crop Growth Model (CGM), Radiative Transfer Model (RTM), and Machine Learning Algorithm (MLA) for estimating crop traits represents a cutting-edge area of research.
Rana Ahmad Faraz Ishaq, Guanhua Zhou, Aamir Ali, Syed Roshaan Ali Shah, Cheng Jiang, Zhongqi Ma, Kang Sun, Hongzhi Jiang   +7 more
doaj   +1 more source

A Two-Stage Short-Term Load Forecasting Method Using Long Short-Term Memory and Multilayer Perceptron

Energies, 2021
Load forecasting is an essential task in the operation management of a power system. Electric power companies utilize short-term load forecasting (STLF) technology to make reasonable power generation plans.
Yuhong Xie, Yuzuru Ueda, Masakazu Sugiyama   +2 more
doaj   +1 more source

Hybrid Modeling of Plasmas [PDF]

, 2010
5 pages, LaTeX; Submitted to the Proceedings of the 8th European Conference on Numerical Mathematics and Advanced Applications, 2009; Small language ...
openaire   +2 more sources

On A nonstandard model of hybrid automaton

2010 IEEE International Conference on Control Applications, 2010
In this paper, we introduce an enlargement of a standard hybrid automaton (HA) called a nonstandard hybrid automaton (NHA) which is another model of HA in the domain of *ℝ rather than ℝ. We define two kinds of almost periodic trajectories called the z-*cycle and p-* cycle on NHA, and we discuss a slightly extended Zeno (*Zeno) and a limit cycle in ...
Nakamura, Katsunori, Fusaoka, Akira
openaire   +2 more sources

Nephrogenic Rests/Nephroblastomatosis in Patients With Unilateral Wilms Tumor Are Not Associated With an Increased Risk of Relapse: An Analysis of Patients Treated on the SIOP‐WT‐2001 Protocol in the SIOP‐UK‐CCLG and SIOP‐GPOH Studies (2001–2022)

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Introduction Nephrogenic rests (NRs) and nephroblastomatosis (NBM) are precursor lesions for development of Wilms tumor (WT). Their association with the risk of relapse has not been properly assessed, partly due to misunderstanding of their diagnostic criteria and terminology.
Gordan M. Vujanić, Rhoikos Furtwängler, Tanzina Chowdhury, Christian Vokuhl, Jenny Wegert, Norbert Graf   +5 more
wiley   +1 more source

A Hybrid Deep Learning Approach for Secure Biometric Authentication Using Fingerprint Data

Computers
Despite significant advancements in fingerprint-based authentication, existing models still suffer from challenges such as high false acceptance and rejection rates, computational inefficiency, and vulnerability to spoofing attacks.
Abdulrahman Hussian, Foud Murshed, Mohammed Nasser Alandoli, Ghalib Aljafari   +3 more
doaj   +1 more source