DeFACT in ManuVerse for parallel manufacturing: Foundation models and parallel workers in smart factories
J Yang, S Li, X Wang, J Lu, H Wu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In cyber–physical–social systems, smart manufacturing has to overcome challenges, such
as uncertainty, diversity, complexity in modeling, long-delayed responses to market …
as uncertainty, diversity, complexity in modeling, long-delayed responses to market …
Deep hypergraph autoencoder embedding: An efficient intelligent approach for rotating machinery fault diagnosis
Intelligent fault diagnosis based on deep learning (DL) has been widely used in various
engineering practices. However, when confronting massive unlabeled industrial data …
engineering practices. However, when confronting massive unlabeled industrial data …
[HTML][HTML] A hybrid framework based on extreme learning machine, discrete wavelet transform, and autoencoder with feature penalty for stock prediction
Accurate prediction of the stock market trend can assist efficient portfolio and risk
management. In recent years, with the rapid development of deep learning, it can make the …
management. In recent years, with the rapid development of deep learning, it can make the …
Laplacian-based dimensionality reduction including spectral clustering, Laplacian eigenmap, locality preserving projection, graph embedding, and diffusion map …
This is a tutorial and survey paper for nonlinear dimensionality and feature extraction
methods which are based on the Laplacian of graph of data. We first introduce adjacency …
methods which are based on the Laplacian of graph of data. We first introduce adjacency …
A hybrid method based on extreme learning machine and wavelet transform denoising for stock prediction
The trend prediction of the stock is a main challenge. Accidental factors often lead to short-
term sharp fluctuations in stock markets, deviating from the original normal trend. The short …
term sharp fluctuations in stock markets, deviating from the original normal trend. The short …
Genetic algorithm-based ensemble hybrid sparse ELM for grasp stability recognition with multimodal tactile signals
Grasp stability recognition based on tactile perception has attracted increasing attention in
the robotics community. In this article, we extract tactile features from multimodal tactile …
the robotics community. In this article, we extract tactile features from multimodal tactile …
Stacked encoded cascade error feedback deep extreme learning machine network for manufacturing order completion time
In this paper, a novel stacked encoded cascade error feedback deep extreme learning
machine (SEC-E-DELM) network is proposed to predict order completion time (OCT) …
machine (SEC-E-DELM) network is proposed to predict order completion time (OCT) …
Explainable AI to understand study interest of engineering students
Students are the future of a nation. Personalizing student interests in higher education
courses is one of the biggest challenges in higher education. Various AI and ML approaches …
courses is one of the biggest challenges in higher education. Various AI and ML approaches …
So many heads, so many Wits: Multimodal graph reasoning for text-based visual question answering
W Zheng, L Yan, FY Wang - IEEE Transactions on Systems …, 2023 - ieeexplore.ieee.org
While texts related to images convey fundamental messages for scene understanding and
reasoning, text-based visual question answering tasks concentrate on visual questions that …
reasoning, text-based visual question answering tasks concentrate on visual questions that …
[HTML][HTML] On the use of high-order feature propagation in Graph Convolution Networks with Manifold Regularization
F Dornaika - Information Sciences, 2022 - Elsevier
Abstract Graph Convolutional Networks (GCNs) have received a lot of attention in pattern
recognition and machine learning. In this paper, we present a revisited scheme for the new …
recognition and machine learning. In this paper, we present a revisited scheme for the new …