Results 261 to 270 of about 4,818,434 (320)

Multivariate Time Series Forecasting Based on Elastic Net and High-Order Fuzzy Cognitive Maps: A Case Study on Human Action Prediction Through EEG Signals

IEEE transactions on fuzzy systems, 2021
Fuzzy cognitive maps (FCMs) have been successfully applied to time series forecasting. However, it still remains challenging to handle multivariate long nonstationary time series, such as EEG data, which may change rapidly and have patterns of trend.
Fang Shen, Jing Liu, Kai Wu
semanticscholar   +1 more source

Robust Elastic-Net Subspace Representation

IEEE Transactions on Image Processing, 2016
Recently, finding the low-dimensional structure of high-dimensional data has gained much attention. Given a set of data points sampled from a single subspace or a union of subspaces, the goal is to learn or capture the underlying subspace structure of the data set.
, Eunwoo Kim, , Minsik Lee, , Songhwai Oh   +2 more
openaire   +2 more sources

Elastic Net Nonparallel Hyperplane Support Vector Machine and Its Geometrical Rationality

IEEE Transactions on Neural Networks and Learning Systems, 2021
Twin support vector machine (TWSVM), which constructs two nonparallel classifying hyperplanes, is widely applied to various fields. However, TWSVM solves two quadratic programming problems (QPPs) separately such that the final classifiers lack ...
Kai Qi, Hu Yang
semanticscholar   +1 more source

Self-Optimizing Support Vector Elastic Net

Analytical Chemistry, 2020
Chemometrics is widely used to solve various quantitative and qualitative problems in analytical chemistry. A self-optimizing chemometrics method facilitates scientists to exploit the advantages of chemometrics. In this report, a parameter-free support vector elastic net that self-optimizes two key regularization constants, i.e., λ for L2 ...
Zewei Chen, Peter de Boves Harrington
openaire   +2 more sources

A robust elastic net-ℓ 1 ℓ 2 reconstruction method for x-ray luminescence computed tomography

Physics in Medicine and Biology, 2021
Objective. X-ray luminescence computed tomography (XLCT) has played a crucial role in pre-clinical research and effective diagnosis of disease. However, due to the ill-posed of the XLCT inverse problem, the generalization of reconstruction methods and ...
Jingwen Zhao, Hongbo Guo, Jingjing Yu, Huangjian Yi, Yuqing Hou, Xiaowei He   +5 more
semanticscholar   +1 more source

A new bearing fault diagnosis method using elastic net transfer learning and LSTM

Journal of Intelligent & Fuzzy Systems, 2021
Although the existing transfer learning method based on deep learning can realize bearing fault diagnosis under variable load working conditions, it is difficult to obtain bearing fault data and the training data of fault diagnosis model is insufficient£¬
Xudong Song, Dajie Zhu, Pan Liang, Lu An
semanticscholar   +1 more source

Robust Monitoring and Fault Isolation of Nonlinear Industrial Processes Using Denoising Autoencoder and Elastic Net

IEEE Transactions on Control Systems Technology, 2020
Robust process monitoring and reliable fault isolation in industrial processes usually encounter different challenges, including process nonlinearity and noise interference.
Wanke Yu, Chunhui Zhao
semanticscholar   +1 more source

The Performance of Ridge Regression, LASSO, and Elastic-Net in Controlling Multicollinearity: A Simulation and Application

Journal of Modern Applied Statistical Methods
This research aims to compare the performance of Ordinary Least Square (OLS), Least Absolute Shrinkage and Selection Operator (LASSO), Ridge Regression (RR) and Elastic-Net in controlling multicollinearity problems between independent variables in ...
Netti Herawati, Ameliana Wijayanti, Agus Sutrisno, Nusyirwan, Misgiyati   +4 more
semanticscholar   +1 more source

Can Ridge and Elastic Net Structural Equation Modeling be Used to Stabilize Parameter Estimates when Latent Factors are Correlated?

Structural Equation Modeling: A Multidisciplinary Journal, 2021
Multicollinearity between predictors is a common concern in SEM applications. As in linear regression models, high correlations between predictors can lead to unstable parameter estimates (i.e., large standard errors) and reduced statistical power ...
F. Scharf, Jana Pförtner, S. Nestler
semanticscholar   +1 more source

A Non-Equidistant Elastic Net Algorithm

1997
The statistical mechanical derivation by Simic of the Elastic Net Algorithm (ENA) from a stochastic Hopfield neural network is criticized. In our view, the ENA should be considered a dynamic penalty method. Using a linear distance measure, a Non-equidistant Elastic Net Algorithm (NENA) is presented.
van den Berg, J (Jan), Geselschap, JH
openaire   +2 more sources