Results 231 to 240 of about 121,348 (314)

Window Impulsive Consensus of Time‐Varying Multi‐Agent Systems Under Deception Attacks on Time Scales

IET Control Theory &Applications, Volume 20, Issue 1, January/December 2026.
This paper investigates the security consensus of time‐varying multi‐agent systems (MASs) on time scales, introducing Bernoulli‐distributed random variables to model node attacks and their probabilities. By proposing a control method combining data sampling and time‐varying window impulses, it relaxes fixed impulsive timing constraints, reduces ...
Boling Zhou, Yongqing Yang, Qi Chang, Yu Jiao, Rixu Hao, Haifei Zhang, Yangling Wang   +6 more
wiley   +1 more source

Radiomics Reproducibility in Prostate Cancer Diagnosis Based on PROSTATEx. [PDF]

Int Neurourol J
Jung S, Kim JS.
europepmc   +1 more source

The spectrum of the Laplacian matrix of a balanced binary tree

, 2002
Óscar Rojo
openalex   +2 more sources

Unscented Kalman Filter With Enhanced Generalised Cross Correlation Entropy for Robust State Estimation of Power System

IET Energy Systems Integration, Volume 8, Issue 1, January/December 2026.
ABSTRACT To solve the complex scenarios, such as multimodal noise, bad measurement data and sudden load changes, in the power system, the enhanced generalised cross correlation entropy unscented Kalman filter (EnGCCE‐UKF) method is proposed in this paper.
Liangzheng Wu, Taofei Ku, Kaiman Li, Peifeng Chen   +3 more
wiley   +1 more source

Sparse Manifold Learning based on Laplacian Matrix

Journal of Physics: Conference Series, 2019
openaire   +1 more source

Ultra‐Short‐Term Wind Speed Prediction Based on Information Aggregation With Spatial Decoupling in Turbine Cluster Space

IET Renewable Power Generation, Volume 20, Issue 1, January/December 2026.
Core approach: hybrid model combining wake dynamics, spectral clustering and adaptive neighbourhood selection. Methodology: spatial decoupling → representative turbine identification → feature aggregation via memory network. Outcome: enhanced prediction accuracy validated by real‐data comparisons, addressing spatial correlation challenges in wind farms.
Xiaofeng Zhu, Zhenxin Li, Chenghan Hou, Shoukun Zou   +3 more
wiley   +1 more source

Machine learning predictions from unpredictable chaos. [PDF]

J R Soc Interface
Jiang J, Chen L, Ke L, Dou B, Zhu Y, Shi Y, Qiu H, Zhang BG, Zhou T, Wei GW.   +9 more
europepmc   +1 more source

Interpretable Multi‐Turbine Output Prediction of Offshore Wind Farms Based on FAGTTN Model

IET Renewable Power Generation, Volume 20, Issue 1, January/December 2026.
This paper proposes a power prediction model feature attention graph convolutional neural network with temporal transformers (FAGTTN) for offshore wind farms based on the feature attention module, adaptive graph convolutional neural network (AGCN) and temporal transformers.
Xiangjing Su, Yizhuo Wang, Junhao Gong, Zhengyu Liu, Yang Fu, Zhaoyang Dong   +5 more
wiley   +1 more source

A Laplacian-based framework for finite element human body model positioning. [PDF]

Front Bioeng Biotechnol
Chen S, Li X.
europepmc   +1 more source

Affine‐Image‐Driven and Finite‐Time Stable Formation Control for Multi‐AUV Systems With Unknown Complex Disturbances: A Geometric Perspective

IET Signal Processing, Volume 2026, Issue 1, 2026.
Formation control of multi‐autonomous underwater vehicle (AUV) systems is essential for collaborative ocean tasks such as environmental monitoring and resource exploration, but it is hindered by challenges like limited flexibility in formation transformation, model uncertainties, and unknown ocean current disturbances.
Fan Luan, Ping Zhang, Xiasheng Shi, Li Chai   +3 more
wiley   +1 more source