An improved Wavenet network for multi-step-ahead wind energy forecasting

Y Wang, T Chen, S Zhou, F Zhang, R Zou… - Energy Conversion and …, 2023 - Elsevier
Accurate multi-step-ahead wind speed (WS) and wind power (WP) forecasting are critical to
the scheduling, planning, and maintenance of wind farms. Previous forecasting methods …

A review of deep learning methods for digitisation of complex documents and engineering diagrams

L Jamieson, C Francisco Moreno-García… - Artificial Intelligence …, 2024 - Springer
This paper presents a review of deep learning on engineering drawings and diagrams.
These are typically complex diagrams, that contain a large number of different shapes, such …

Component segmentation of engineering drawings using Graph Convolutional Networks

W Zhang, J Joseph, Y Yin, L Xie, T Furuhata… - Computers in …, 2023 - Elsevier
We present a data-driven framework to automate the vectorization and machine
interpretation of 2D engineering part drawings. In industrial settings, most manufacturing …

[HTML][HTML] Smart Techniques Promoting Sustainability in Construction Engineering and Management

SS Lin, SL Shen, A Zhou, XS Chen - Engineering, 2024 - Elsevier
Construction engineering and management (CEM) has become increasingly complicated
with the increasing size of engineering projects under different construction environments …

[HTML][HTML] Multi-view expressive graph neural networks for 3D CAD model classification

S Li, J Corney - Computers in Industry, 2023 - Elsevier
The creation of effective content-based retrieval systems for the 3D models of engineering
components created by Mechanical Computer Aided Design (MCAD) systems has been a …

Boosting short term electric load forecasting of high & medium voltage substations with visibility graphs and graph neural networks

N Giamarelos, EN Zois - Sustainable Energy, Grids and Networks, 2024 - Elsevier
Modern power grids are faced with a series of challenges, such as the ever-increasing
demand for renewable energy sources, extensive urbanization, climate and energy crisis …

BIGNet: A Deep Learning Architecture for Brand Recognition with Geometry-Based Explainability

Y Chen, LB Kara, J Cagan - Journal of …, 2024 - asmedigitalcollection.asme.org
Incorporating style-related objectives into shape design has been centrally important to
maximize product appeal. However, algorithmic style capture and reuse have not fully …

Optical character recognition on engineering drawings to achieve automation in production quality control

J Villena Toro, A Wiberg, M Tarkian - Frontiers in Manufacturing …, 2023 - frontiersin.org
Introduction: Digitization is a crucial step towards achieving automation in production quality
control for mechanical products. Engineering drawings are essential carriers of information …

LABAMPsGCN: A framework for identifying lactic acid bacteria antimicrobial peptides based on graph convolutional neural network

TJ Sun, HL Bu, X Yan, ZH Sun, MS Zha… - Frontiers in …, 2022 - frontiersin.org
Lactic acid bacteria antimicrobial peptides (LABAMPs) are a class of active polypeptide
produced during the metabolic process of lactic acid bacteria, which can inhibit or kill …

A method for detecting process design intent in the process route based on heterogeneous graph convolutional networks

J Liang, S Zhang, C Xu, Y Zhang, R Huang… - Robotics and Computer …, 2025 - Elsevier
The process design intent is the concentration of the technologists' design cognitive process
which contains the experiential knowledge and skills. It can reproduce technologists' design …