Prediction of Binder Content in Glass Fiber Reinforced Asphalt Mix Using Machine Learning Techniques-Reference-Cited by-同舟云学术

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Prediction of Binder Content in Glass Fiber Reinforced Asphalt Mix Using Machine Learning Techniques

Published:2022 Issue: Volume:10 Page:33866-33881
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Upadhya Ankita¹,Thakur M. S.¹^ORCID,Mashat Arwa²^ORCID,Gupta Gaurav³^ORCID,Abdo Mohammed S.⁴^ORCID

Affiliation:

1. Department of Civil Engineering, Shoolini University, Solan, Himachal Pradesh, India

2. Faculty of Computing and Information Technology, King Abdulaziz University, Rabigh, Saudi Arabia

3. Yogananda School of Artificial Intelligence, Computer and Data Sciences, Shoolini University, Solan, Himachal Pradesh, India

4. Department of Mathematics, Hodeidah University, Al Hudaydah, Yemen

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09729824.pdf?arnumber=9729824

Reference61 articles.

1. Modeling corrosion currents of reinforced concrete using ANN

2. Prediction of compressive strength of heavyweight concrete by ANN and FL models

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2. Soft computing-based optimization of plastic waste utilization in flexible pavement construction;Multiscale and Multidisciplinary Modeling, Experiments and Design;2024-03-21

3. Non-Destructive Evaluation of Strength and Porosity of Bituminous Mixes Using Log- Periodic Feedlines-Based Ring Filter;IEEE Transactions on Instrumentation and Measurement;2024

4. Influence of hybrid fibers on rheological properties of asphalt binders and its prediction with computing techniques;Construction and Building Materials;2023-10

5. Multiscale Modeling and Data-Driven Approaches for Energy Efficiency Prediction in Computing;2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA);2023-08-03

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