Machine Learning and Artificial Intelligence Applications in Building Construction: Present Status and Future Trends-Reference-Cited by-同舟云学术

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Machine Learning and Artificial Intelligence Applications in Building Construction: Present Status and Future Trends

Published:2022-03-07 Issue: Volume: Page:
ISSN:
Container-title:Construction Research Congress 2022
language:
Short-container-title:

Author:

Ensafi Mahnaz¹²³⁴,Alimoradi Saeid¹²³⁴,Gao Xinghua¹²³⁴,Thabet Walid¹²³⁴

Affiliation:

1. Ph.D. Candidate, Dept. of Building Construction, Virginia Polytechnic Institute and State Univ., Blacksburg, VA.

2. Ph.D. Student, Dept. of Building Construction, Virginia Polytechnic Institute and State Univ., Blacksburg, VA.

3. Assistant Professor, Dept. of Building Construction, Virginia Polytechnic Institute and State Univ., Blacksburg, VA.

4. Professor, Dept. of Building Construction, Virginia Polytechnic Institute and State Univ., Blacksburg, VA.

Publisher

American Society of Civil Engineers

Link

https://ascelibrary.org/doi/pdf/10.1061/9780784483961.013

Reference37 articles.

1. Smartphone-based construction workers' activity recognition and classification

2. Deep Learning in the Construction Industry: A Review of Present Status and Future Innovations;Akinosho T. D.;Journal of Building Engineering,2020

3. Automated detection and classification of construction workers' loss of balance events using wearable insole pressure sensors

4. A deep‐learning‐based computer vision solution for construction vehicle detection

5. Data-Driven Machine Learning Approach to Integrate Field Submittals in Project Scheduling

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1. Work order prioritization using neural networks to improve building operation;Journal of Information Technology in Construction;2024-04-18

2. A Computer Vision Approach to Assessing Work-Related Musculoskeletal Disorder (WMSD) Risk in Construction Workers;Construction Research Congress 2024;2024-03-18

3. Developing a Machine-Learning Model to Predict Clash Resolution Options;Journal of Computing in Civil Engineering;2024-03

4. Investigation of work order processing in different facilities: a questionnaire-based survey;Facilities;2024-01-30

5. Using Hybrid Artificial Intelligence Optimization Method to Predict Construction Labour Productivity;Lecture Notes in Civil Engineering;2023

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