Scientific Research Publishing

A Review of Data-Driven Prediction of Undesirable Events in Offshore Oil Wells

The production and operation of offshore oil wells present typical characteristics of strong coupling, high nonlinearity, obvious time-varying behavior, and high operational risks. The occurrence of ...
IEEE

A Graph Convolutional Encoder-Decoder Model for Methane Concentration Forecasting in Coal Mines

Abstract: Methane is one of the most dangerous gases produced in the process of coal mining. Because of its flammable and explosive characteristics, it has seriously threatened the life and property ...
IEEE

Self-Attention Based Multi-Scale Graph Auto-Encoder Network of 3D Meshes

Abstract: 3D meshes are fundamental data representations for capturing complex geometric shapes in computer vision and graphics applications. While Convolutional Neural Networks (CNNs) have excelled ...
Frontiers

Association prediction of lncRNAs and diseases using multiview graph convolution neural network

Long noncoding RNAs (lncRNAs) regulate physiological processes via interactions with macromolecules such as miRNAs, proteins, and genes, forming disease-associated regulatory networks. However, ...
Scientific Research Publishing

Phan, A.V., Nguyen, M.L., Nguyen, Y.L.H. and Bui, L.T. (2018) DGCNN: A Convolutional Neural Network over Large-Scale Labeled Graphs. Neural Networks, 108, 533-543.

ABSTRACT: Point cloud-based 3D object detection is a key technology in autonomous driving and mobile robot perception systems. However, the sparsity and irregularity of point cloud data result in poor ...