Prediction models for marshall mix parameters using bio-inspired genetic programming and deep machine learning approaches: A comparative study

This research study utilizes four machine learning techniques, i.e., Multi Expression programming (MEP), Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Ensemble Decision Tree Bagging (DT-Bagging) for the development of new and advanced models for prediction of Ma...

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Veröffentlicht in:	Case Studies in Construction Materials Jg. 18; S. e01774
Hauptverfasser:	Althoey, Fadi, Akhter, Muhammad Naveed, Nagra, Zohaib Sattar, Awan, Hamad Hassan, Alanazi, Fayez, Khan, Mohsin Ali, Javed, Muhammad Faisal, Eldin, Sayed M., Özkılıç, Yasin Onuralp
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.07.2023 Elsevier
Schlagworte:	Asphalt Bio-Inspired models Deep Learning Marshall Mix Parameter Prediction models Bio-Inspired models Asphalt Prediction models Marshall Mix Parameter Deep Learning
ISSN:	2214-5095, 2214-5095
Online-Zugang:	Volltext
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