Advances in the dynamics of origami structures and origami metamaterials
F Hongbin, W Hai**, L Zuolin, Z Qiwei… - Chinese Journal of …, 2022 - lxxb.cstam.org.cn
Recently, due to the infinite design space, outstanding capability in changing shape,
dimension, and topology, as well as the folding-induced extraordinary mechanical …
dimension, and topology, as well as the folding-induced extraordinary mechanical …
Forecasting short-term subway passenger flow under special events scenarios using multiscale radial basis function networks
Reliable and accurate short-term subway passenger flow prediction is important for
passengers, transit operators, and public agencies. Traditional studies focus on regular …
passengers, transit operators, and public agencies. Traditional studies focus on regular …
Wavelet neural networks: A practical guide
Wavelet networks (WNs) are a new class of networks which have been used with great
success in a wide range of applications. However a general accepted framework for …
success in a wide range of applications. However a general accepted framework for …
Short-term passenger flow prediction under passenger flow control using a dynamic radial basis function network
Short-term passenger flow prediction and passenger flow control are essential for managing
congestion in metros. This paper proposes a new dynamic radial basis function (RBF) …
congestion in metros. This paper proposes a new dynamic radial basis function (RBF) …
A new class of wavelet networks for nonlinear system identification
SA Billings, HL Wei - IEEE Transactions on neural networks, 2005 - ieeexplore.ieee.org
A new class of wavelet networks (WNs) is proposed for nonlinear system identification. In the
new networks, the model structure for a high-dimensional system is chosen to be a …
new networks, the model structure for a high-dimensional system is chosen to be a …
Epileptic seizure detection in EEG signals using sparse multiscale radial basis function networks and the Fisher vector approach
Detecting epileptic seizures in electroencephalography (EEG) signals is a challenging task
due to nonstationary processes of brain activities. Currently, the epilepsy is mainly detected …
due to nonstationary processes of brain activities. Currently, the epilepsy is mainly detected …
Feature subset selection and ranking for data dimensionality reduction
HL Wei, SA Billings - IEEE transactions on pattern analysis and …, 2006 - ieeexplore.ieee.org
A new unsupervised forward orthogonal search (FOS) algorithm is introduced for feature
selection and ranking. In the new algorithm, features are selected in a stepwise way, one at …
selection and ranking. In the new algorithm, features are selected in a stepwise way, one at …
Exploring determinants of housing prices: A case study of Chinese experience in 1999–2010
How do macroeconomic variables affect housing prices? In this paper we apply a non-linear
modeling approach, the Nonlinear Auto Regressive Moving Average with eXogenous inputs …
modeling approach, the Nonlinear Auto Regressive Moving Average with eXogenous inputs …
Forecasting peak air pollution levels using NARX models
Air pollution has a negative impact on human health. For this reason, it is important to
correctly forecast over-threshold events to give timely warnings to the population. Nonlinear …
correctly forecast over-threshold events to give timely warnings to the population. Nonlinear …
Application of nonlinear time series and machine learning algorithms for forecasting groundwater flooding in a lowland karst area
In karst limestone areas interactions between ground and surface waters can be frequent,
particularly in low lying areas, linked to the unique hydrogeological dynamics of that bedrock …
particularly in low lying areas, linked to the unique hydrogeological dynamics of that bedrock …