Suchergebnisse - "Multi-expression programming"

Predicting 28-day compressive strength of fibre-reinforced self-compacting concrete (FR-SCC) using MEP and GEP

Autoren: Inqiad, Waleed Bin Siddique, Muhammad Shahid Ali, Mujahid et al.

Quelle: Scientific Reports. 14

Schlagwörter: Fiber-reinforced self-compacting concrete, Gene expression programming, Genetic Programming, Multi expression programming, Self-compacting concrete, Operation and Maintenance Engineering, Drift och underhållsteknik

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-108491
https://doi.org/10.1038/s41598-024-65905-5

Predictive modeling for depth of wear of concrete modified with fly ash: A comparative analysis of genetic programming-based algorithms

Autoren: Khan, Adil Khan, Majid Ali, Mohsin et al.

Quelle: Case Studies in Construction Materials. 20

Schlagwörter: Fly ash, Abrasion resistance, Gene expression programming, Multi-expression programming, SHAP, Operation and Maintenance Engineering, Drift och underhållsteknik

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-103256
https://doi.org/10.1016/j.cscm.2023.e02744

Intelligent prediction modeling for flexural capacity of FRP-strengthened reinforced concrete beams using machine learning algorithms

Autoren: Khan, Majid Khan, Adil Khan, Asad Ullah et al.

Quelle: Heliyon. 10(1)

Schlagwörter: Fiber-reinforced polymers, Flexural capacity, Machine learning, Gene expression programming, Multi-expression programming, Operation and Maintenance Engineering, Drift och underhållsteknik

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-103262
https://doi.org/10.1016/j.heliyon.2023.e23375

Predicting strength in polypropylene fiber reinforced rubberized concrete using symbolic regression AI techniques

Autoren: Ahmed A. Alawi Al-Naghi Kinza Aamir Muhammad Nasir Amin et al.

Quelle: Case Studies in Construction Materials, Vol 23, Iss , Pp e05024- (2025)

Schlagwörter: Rubberized concrete, Polypropylene fiber, Gene expression programming, Multi-expression programming, SHAP analysis, Sensitivity analysis, Materials of engineering and construction. Mechanics of materials, TA401-492

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2214509525008228; https://doaj.org/toc/2214-5095

Zugangs-URL: https://doaj.org/article/7d741245dff0483a9bc92077dd9ee713

Analyzing the viability of agro-waste for sustainable concrete: Expression-based formulation and validation of predictive models for strength performance

Autoren: Alsharari Fahad Nassar Roz-Ud-Din Alshammari Talal O. et al.

Quelle: Reviews on Advanced Materials Science, Vol 64, Iss 1, Pp id. 127828-1710 (2025)

Schlagwörter: agricultural waste-based concrete, gene and multi expression programming, compressive and tensile strength, Technology, Chemical technology, TP1-1185

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1605-8127

Zugangs-URL: https://doaj.org/article/9fda902b68b048d3a0a18e3557c423e8

Comparative analysis of various machine learning algorithms to predict 28-day compressive strength of Self-compacting concrete

Autoren: Inqiad, Waleed Bin Siddique, Muhammad Shahid Alarifi, Saad S. et al.

Quelle: Heliyon. 9(11)

Schlagwörter: Machine learning (ML), Self-compacting concrete (SCC), 28-Day compressive strength (C–S), Multi expression programming (MEP), Extreme gradient boosting (XGB), Random forest (RF), Operation and Maintenance Engineering, Drift och underhållsteknik

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-102670
https://doi.org/10.1016/j.heliyon.2023.e22036

Leveraging waste-based additives and machine learning for sustainable mortar development in construction

Autoren: Zhang Yi Zhang Qizhi Alqurashi Muwaffaq et al.

Quelle: Reviews on Advanced Materials Science, Vol 64, Iss 1, Pp pp. 453-465 (2025)

Schlagwörter: rubberized mortar, sustainable construction materials, gene and multi-expression programming, Technology, Chemical technology, TP1-1185

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1605-8127

Zugangs-URL: https://doaj.org/article/15430320318c4d499654cdb384df1ade

Evaluating the dynamic response and phase angle behavior of SBS-modified asphalt mixtures for enhanced pavement performance

Autoren: Inamullah Khan Muhammad Bilal Wasim Khaliq et al.

Quelle: Scientific Reports, Vol 14, Iss 1, Pp 1-26 (2024)

Schlagwörter: Styrene butadiene styrene (SBS), Dynamic modulus, Phase angle, Multi expression programming, Sensitivity analysis, Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2045-2322

Zugangs-URL: https://doaj.org/article/ec3d9b03c2874b96a1ba7f22b9bd5ff3

Development of predictive models for sustainable concrete via genetic programming-based algorithms

Autoren: Lingling Chen Zhiyuan Wang Aftab Ahmad Khan et al.

Quelle: Journal of Materials Research and Technology, Vol 24, Iss, Pp 6391-6410 (2023)

Schlagwörter: Composite material, Generalization, FOS: Mechanical engineering, Genetic programming, Mathematical analysis, Multi-expression programming, 12. Responsible consumption, Engineering, Foundry, Machine learning, Gene expression programming, FOS: Mathematics, Sustainable construction, Casting, 2. Zero hunger, Mining engineering. Metallurgy, Mechanical Engineering, Waste Utilization, TN1-997, Building and Construction, 15. Life on land, Computer science, Materials science, Solid waste, Recycling and Utilization of Foundry Waste Materials, 3D Concrete Printing Technology, Algorithm, Waste foundry sand, Aggregate (composite), Ultimate tensile strength, Physical Sciences, Metallurgy, Mathematics

Zugangs-URL: https://doaj.org/article/2c19f4157dac4a5783e01fb212c785c8

Crack width prediction of self-healing engineered cementitious composite using multi-expression programming

Autoren: Fadi Althoey Nadhim Hamah Sor Haitham M. Hadidi et al.

Quelle: Journal of Materials Research and Technology, Vol 24, Iss, Pp 918-927 (2023)

Schlagwörter: Mining engineering. Metallurgy, Self-healing, TN1-997, 0211 other engineering and technologies, Engineering cementitious composites, 02 engineering and technology, Parametric analysis, Multi-expression programming, 0201 civil engineering

Zugangs-URL: https://doaj.org/article/11914d1a5b824d7cb58f622d9f2c614a

Data-driven evolutionary programming for evaluating the mechanical properties of concrete containing plastic waste

Autoren: Usama Asif Muhammad Faisal Javed Deema Mohammed Alsekait et al.

Quelle: Case Studies in Construction Materials, Vol 21, Iss , Pp e03763- (2024)

Schlagwörter: Plastic waste concrete, Compressive strength, Gene expression programming, Multi-expression programming, Tensile strength, Sustainable development, Materials of engineering and construction. Mechanics of materials, TA401-492

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2214509524009148; https://doaj.org/toc/2214-5095

Zugangs-URL: https://doaj.org/article/310559ded5a941bb9088e387c0a3112e

Predicting compressive strength of hollow concrete prisms using machine learning techniques and explainable artificial intelligence (XAI)

Autoren: Waleed Bin Inqiad Elena Valentina Dumitrascu Robert Alexandru Dobre et al.

Quelle: Heliyon, Vol 10, Iss 17, Pp e36841- (2024)

Schlagwörter: Concrete masonry prisms, Machine learning, Multi expression programming, Compressive strength, Explainable artificial intelligence (XAI), Science (General), Q1-390, Social sciences (General), H1-99

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2405844024128721; https://doaj.org/toc/2405-8440

Zugangs-URL: https://doaj.org/article/9a81a7096e754f6ab47ba05310250c60

Toward sustainability: Integrating experimental study and data-driven modeling for eco-friendly paver blocks containing plastic waste

Autoren: Asif Usama Javed Muhammad Faisal Alsekait Deema Mohammed et al.

Quelle: Reviews on Advanced Materials Science, Vol 63, Iss 1, Pp id. 137512-921 (2024)

Schlagwörter: compressive strength, plastic waste, basalt fiber, multi-expression programming, paver blocks, graphical user interface, Technology, Chemical technology, TP1-1185

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1605-8127

Zugangs-URL: https://doaj.org/article/c1da7777499746aaabcfaac83b608c1e

Dataset used to develop soft computing models that predict the stiffness modulus of bituminous mixtures

Autoren: Lee P. Leon Hector Martin Upaka Rathnayake et al.

Quelle: Data in Brief, Vol 54, Iss , Pp 110382- (2024)

Schlagwörter: Asphalt concrete, Gene expression programming, Pavement design, Indirect tensile stiffness modulus, Multi expression programming, Pavement materials, Computer applications to medicine. Medical informatics, R858-859.7, Science (General), Q1-390

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2352340924003512; https://doaj.org/toc/2352-3409

Zugangs-URL: https://doaj.org/article/731aa9018e564d95bbeb13022a1cac1e

Compressive strength of waste-derived cementitious composites using machine learning

Autoren: Tian Qiong Lu Yijun Zhou Ji et al.

Quelle: Reviews on Advanced Materials Science, Vol 63, Iss 1, Pp id. 126-573 (2024)

Schlagwörter: marble cement, gene expression programming, multi-expression programming, Technology, Chemical technology, TP1-1185

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/1605-8127

Zugangs-URL: https://doaj.org/article/997426993f224dc48c30f0fa368790e8

Sustainable use of fly-ash: Use of gene-expression programming (GEP) and multi-expression programming (MEP) for forecasting the compressive strength geopolymer concrete

Autoren: Adeel Zafar M. Ijaz Khan Hong-Hu Chu et al.

Quelle: Ain Shams Engineering Journal, Vol 12, Iss 4, Pp 3603-3617 (2021)

Schlagwörter: Multi expression programming (MEP), Fly-ash, 0211 other engineering and technologies, 02 engineering and technology, Engineering (General). Civil engineering (General), Artificial intelligence (AI), 7. Clean energy, 12. Responsible consumption, 0201 civil engineering, 13. Climate action, Waste material, 11. Sustainability, Gene expression programming (GEP), TA1-2040, Geopolymer concrete (GPC)

Zugangs-URL: https://doaj.org/article/5a4058d33bd748e8b41479e25320ab54
https://www.sciencedirect.com/science/article/pii/S2090447921001830
https://www.sciencedirect.com/science/article/abs/pii/S2090447921001830

Optimizing compressive strength prediction models for rice husk ash concrete with evolutionary machine intelligence techniques

Autoren: Muhammad Nasir Amin Waqas Ahmad Kaffayatullah Khan et al.

Quelle: Case Studies in Construction Materials, Vol 18, Iss , Pp e02102- (2023)

Schlagwörter: Rice husk ash, Sustainable concrete, Gene expression programming, Multi-expression programming, SHapley Additive exExplanations, Materials of engineering and construction. Mechanics of materials, TA401-492

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2214509523002826; https://doaj.org/toc/2214-5095

Zugangs-URL: https://doaj.org/article/04ff5715e6534e079f919f3ae46e49bc

Straightforward prediction for air-entry value of compacted soils using machine learning algorithms

Autoren: Wang, HL Yin, ZY Zhang, P et al.

Weitere Verfasser: Wang, HL Yin, ZY Zhang, P et al.

Schlagwörter: Air-entry value, Compacted soils, Evolutionary polynomial regression, Machine learning, Multi expression programming, Random forest

Relation: http://hdl.handle.net/10397/101037; 279; 105911

Verfügbarkeit: http://hdl.handle.net/10397/101037
https://doi.org/10.1016/j.enggeo.2020.105911

Estimation of 28-Day Compressive Strength of Self-Compacting Concrete Using Multi Expression Programming (MEP): An Artificial Intelligence Approach

Autoren: Waleed Bin Inqiad

Quelle: Engineering Proceedings, Vol 56, Iss 1, p 212 (2023)

Schlagwörter: artificial intelligence (AI), multi-expression programming (MEP), self-compacting concrete (SCC), Engineering machinery, tools, and implements, TA213-215

Relation: https://www.mdpi.com/2673-4591/56/1/212; https://doaj.org/toc/2673-4591; https://doaj.org/article/4d5e7b9c3a8c4d9c9ad36d94b98ce4e2

Verfügbarkeit: https://doi.org/10.3390/ASEC2023-15525
https://doaj.org/article/4d5e7b9c3a8c4d9c9ad36d94b98ce4e2

Unconfined compressive strength of bio-cemented sand: state-of-the-art review and MEP-MC-based model development

Autoren: Wang, HL Yin, ZY Department of Civil and Environmental Engineering

Weitere Verfasser: Wang, HL Yin, ZY Department of Civil and Environmental Engineering

Schlagwörter: Bio-cemented sand, Microbially induced calcite precipitation (MICP), Monte-Carlo (MC) method, Multi expression programming (MEP), Unconfined compressive strength (UCS)

Relation: http://hdl.handle.net/10397/97367; 315; 128205

Verfügbarkeit: http://hdl.handle.net/10397/97367
https://doi.org/10.1016/j.jclepro.2021.128205