UB Paderborn / Katalog / Suche / in CDI

1 – 25 von 77

Sortiert nach

Set-sequential labelings of odd trees

Discussiones Mathematicae. Graph Theory, 2024-01, Vol.44 (1), p.151

2024

Volltextzugriff (PDF)

Constructing bounded degree graphs with prescribed degree and neighbor degree sequences

Discrete Applied Mathematics, 2023-06, Vol.332, p.47-61

2023

Volltextzugriff (PDF)

A systematic literature review on hardware implementation of artificial intelligence algorithms

The Journal of supercomputing, 2021-02, Vol.77 (2), p.1897-1938

2021

Volltextzugriff (PDF)

CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database

Nucleic acids research, 2023-01, Vol.51 (D1), p.D690

2023

Volltextzugriff (PDF)

Nano-Silica-Modified Concrete: A Bibliographic Analysis and Comprehensive Review of Material Properties

Nanomaterials (Basel, Switzerland), 2022-06, Vol.12 (12), p.1989

2022

Volltextzugriff (PDF)

Comparative Study of Experimental and Modeling of Fly Ash-Based Concrete

Materials, 2022-05, Vol.15 (11), p.3762

2022

Volltextzugriff (PDF)

A Scientometric-Analysis-Based Review of the Research Development on Geopolymers

Polymers, 2022-09, Vol.14 (17), p.3676

2022

Volltextzugriff (PDF)

Evaluating the Strength and Impact of Raw Ingredients of Cement Mortar Incorporating Waste Glass Powder Using Machine Learning and SHapley Additive ExPlanations (SHAP) Methods

Materials, 2022-10, Vol.15 (20), p.7344

2022

Volltextzugriff (PDF)

Use of Artificial Intelligence for Predicting Parameters of Sustainable Concrete and Raw Ingredient Effects and Interactions

Materials, 2022-07, Vol.15 (15), p.5207

2022

Volltextzugriff (PDF)

Application of waste recycle tire steel fibers as a construction material in concrete

Reviews on advanced materials science, 2023-07, Vol.62 (1), p.pp. 658-662

2023

Volltextzugriff (PDF)

Analytic hierarchy process to determine process parameters for optimal surface finish and dimensional accuracy

AIP Conference Proceedings, 2023, Vol.2530 (1)

2023

Volltextzugriff (PDF)

Formulation of estimation models for the compressive strength of concrete mixed with nanosilica and carbon nanotubes

Developments in the built environment, 2023-03, Vol.13, p.100113, Article 100113

2023

Volltextzugriff (PDF)

Machine learning interpretable-prediction models to evaluate the slump and strength of fly ash-based geopolymer

Journal of materials research and technology, 2023-05, Vol.24, p.100-124

2023

Volltextzugriff (PDF)

Split Tensile Strength Prediction of Recycled Aggregate-Based Sustainable Concrete Using Artificial Intelligence Methods

Materials, 2022-06, Vol.15 (12), p.4296

2022

Volltextzugriff (PDF)

Post‐pandemic world at the mercy of monkeypox virus outbreak: Time to worry or not?

Journal of medical virology, 2023-01, Vol.95 (1), p.e27948-n/a

2023

Volltextzugriff (PDF)

Assessment of Artificial Intelligence Strategies to Estimate the Strength of Geopolymer Composites and Influence of Input Parameters

Polymers, 2022-06, Vol.14 (12), p.2509

2022

Volltextzugriff (PDF)

Tip of the iceberg: Emergence of Langya virus in the postpandemic world

Journal of medical virology, 2023-01, Vol.95 (1), p.e28173-n/a

2023

Volltextzugriff (PDF)

Exploring the Use of Waste Marble Powder in Concrete and Predicting Its Strength with Different Advanced Algorithms

Materials, 2022-06, Vol.15 (12), p.4108

2022

Volltextzugriff (PDF)

Compressive Strength Estimation of Steel-Fiber-Reinforced Concrete and Raw Material Interactions Using Advanced Algorithms

Polymers, 2022-07, Vol.14 (15), p.3065

2022

Volltextzugriff (PDF)

Predicting the impact of environmental factors on citrus canker through multiple regression

PloS one, 2022-04, Vol.17 (4), p.e0260746-e0260746

2022

Volltextzugriff (PDF)

Predictive modelling of compressive strength of fly ash and ground granulated blast furnace slag based geopolymer concrete using machine learning techniques

Case Studies in Construction Materials, 2024-07, Vol.20, p.e03130, Article e03130

2024

Volltextzugriff (PDF)

Estimation of strength, rheological parameters, and impact of raw constituents of alkali-activated mortar using machine learning and SHapely Additive exPlanations (SHAP)

Construction & building materials, 2023-05, Vol.377, p.131014, Article 131014

2023

Volltextzugriff (PDF)

In-Depth Analysis of Cement-Based Material Incorporating Metakaolin Using Individual and Ensemble Machine Learning Approaches

Materials, 2022-11, Vol.15 (21), p.7764

2022

Volltextzugriff (PDF)

Machine Learning-Based Modeling with Optimization Algorithm for Predicting Mechanical Properties of Sustainable Concrete

Advances in Civil Engineering, 2021, Vol.2021 (1)

2021

Volltextzugriff (PDF)

A data-driven approach to predict the compressive strength of alkali-activated materials and correlation of influencing parameters using SHapley Additive exPlanations (SHAP) analysis

Journal of materials research and technology, 2023-07, Vol.25, p.4074-4093

2023

Volltextzugriff (PDF)

1 – 25 von 77

Suche als RSS-Feed

Suchergebnisse filtern

Filter anzeigen

Nur zeigen

Geprüft (Peer-Review)
(65)
Mit Volltextzugriff
(72)

Publikationsform

Sprache

Erscheinungsjahr

n.n

Thema

Science & Technology
(53)
Technology
(26)
Life Sciences & Biomedicine
(19)
Physical Sciences
(18)
Materials Science
(17)
Materials Science, Multidisciplinary
(17)
Machine Learning
(15)
Compressive Strength
(14)
Algorithms
(12)
Engineering
(12)
Concrete
(11)
Artificial Intelligence
(10)
Chemistry
(9)
Construction & Building Technology
(9)
Engineering, Civil
(9)
Mechanical Properties
(9)
Metallurgy & Metallurgical Engineering
(9)
Cement
(8)
Concrete Properties
(8)
Physics
(8)

15 weitere anzeigen...

Weniger anzeigen...

Neu hinzugefügt

... seit 90 Tagen
(1)

Menü

Weitere Dienste

Einstellungen

Set-sequential labelings of odd trees

Constructing bounded degree graphs with prescribed degree and neighbor degree sequences

A systematic literature review on hardware implementation of artificial intelligence algorithms

CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database

Nano-Silica-Modified Concrete: A Bibliographic Analysis and Comprehensive Review of Material Properties

Comparative Study of Experimental and Modeling of Fly Ash-Based Concrete

A Scientometric-Analysis-Based Review of the Research Development on Geopolymers

Evaluating the Strength and Impact of Raw Ingredients of Cement Mortar Incorporating Waste Glass Powder Using Machine Learning and SHapley Additive ExPlanations (SHAP) Methods

Use of Artificial Intelligence for Predicting Parameters of Sustainable Concrete and Raw Ingredient Effects and Interactions

Application of waste recycle tire steel fibers as a construction material in concrete

Analytic hierarchy process to determine process parameters for optimal surface finish and dimensional accuracy

Formulation of estimation models for the compressive strength of concrete mixed with nanosilica and carbon nanotubes

Machine learning interpretable-prediction models to evaluate the slump and strength of fly ash-based geopolymer

Split Tensile Strength Prediction of Recycled Aggregate-Based Sustainable Concrete Using Artificial Intelligence Methods

Post‐pandemic world at the mercy of monkeypox virus outbreak: Time to worry or not?

Assessment of Artificial Intelligence Strategies to Estimate the Strength of Geopolymer Composites and Influence of Input Parameters

Tip of the iceberg: Emergence of Langya virus in the postpandemic world

Exploring the Use of Waste Marble Powder in Concrete and Predicting Its Strength with Different Advanced Algorithms

Compressive Strength Estimation of Steel-Fiber-Reinforced Concrete and Raw Material Interactions Using Advanced Algorithms

Predicting the impact of environmental factors on citrus canker through multiple regression

Predictive modelling of compressive strength of fly ash and ground granulated blast furnace slag based geopolymer concrete using machine learning techniques

Estimation of strength, rheological parameters, and impact of raw constituents of alkali-activated mortar using machine learning and SHapely Additive exPlanations (SHAP)

In-Depth Analysis of Cement-Based Material Incorporating Metakaolin Using Individual and Ensemble Machine Learning Approaches

Machine Learning-Based Modeling with Optimization Algorithm for Predicting Mechanical Properties of Sustainable Concrete

A data-driven approach to predict the compressive strength of alkali-activated materials and correlation of influencing parameters using SHapley Additive exPlanations (SHAP) analysis

Suchergebnisse filtern