Proposing several hybrid SSA—machine learning techniques for estimating rock cuttability by conical pick with relieved cutting modes

During excavation of roadheader, specific energy (SE) is a key component of rock cuttability evaluation and cutting head design. Previous studies have shown that the specific energy is simultaneously affected by physical and mechanical parameters of rock, pick geometry, and pick operation parameters...

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Veröffentlicht in:	Acta geotechnica Jg. 18; H. 3; S. 1431 - 1446
Hauptverfasser:	Zhou, Jian, Dai, Yong, Huang, Shuai, Armaghani, Danial Jahed, Qiu, Yingui
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2023 Springer Nature B.V
Schlagworte:	Algorithms Angle of attack Artificial neural networks Back propagation networks Complex Fluids and Microfluidics Compressive strength Cutting Cutting parameters Engineering Excavation Foundations Geoengineering Geotechnical Engineering & Applied Earth Sciences Hydraulics Kernel functions Learning algorithms Machine learning Mathematical models Mechanical properties Neural networks Parameters Predictions Rake angle Research Paper Rock Rocks Search algorithms Sediment samples Soft and Granular Matter Soil Science & Conservation Solid Mechanics Specific energy Support vector machines Tensile strength Rock cuttability Specific energy Sparrow search algorithm Machine learning
ISSN:	1861-1125, 1861-1133
Online-Zugang:	Volltext
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