Equipment activity recognition and early fault detection in automated construction through a hybrid machine learning framework-Reference-Cited by-同舟云学术

Equipment activity recognition and early fault detection in automated construction through a hybrid machine learning framework

Published:2022-04-28 Issue:2 Volume:38 Page:253-268
ISSN:1093-9687
Container-title:Computer-Aided Civil and Infrastructure Engineering
language:en
Short-container-title:Computer aided Civil Eng

Author:

Harichandran Aparna¹²^ORCID,Raphael Benny¹^ORCID,Mukherjee Abhijit²^ORCID

Affiliation:

1. Department of Civil Engineering Indian Institute of Technology Madras Chennai India

2. School of Civil and Mechanical Engineering Curtin University Perth Australia

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering,Building and Construction

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/mice.12848

Reference55 articles.

1. Enhanced probabilistic neural network with local decision circles: A robust classifier

2. Construction equipment activity recognition for simulation input modeling using mobile sensors and machine learning classifiers

3. A dynamic ensemble learning algorithm for neural networks

4. A Review of Artificial Intelligence Methods for Condition Monitoring and Fault Diagnosis of Rolling Element Bearings for Induction Motor

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