Suchergebnisse - "Machine Learning Methods"

La creativitat en el futbol com a fenomen complex. Eines d’avaluació i propostes per desenvolupar-la

Autoren: Canton, Albert

Thesis Advisors: Torrents Martín, Carlota, Hristovski, Robert, Institut Nacional d'Educació Física de Catalunya (Lleida)

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: Complexitat, Jocs reduïts, Dynamic overlap, Anàlisi de components principals, Coeficient de congruència de Tucker, Esports d’equip, Unsupervised Machine Learning Methods, Complejidad, Juegos reducidos, Análisis de componentes principales, Coeficiente de congruencia de Tucker, Deportes de equipo, Complexity, Small-sided games, Principal components analysis, Tucker's congruence coefficient, Team sports, Educació Física i Esportiva

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/687552

Creating and Leveraging a Synthetic Dataset of Cloud Optical Thickness Measures for Cloud Detection in MSI

Autoren: Pirinen, Aleksis Abid, Nosheen Agues Paszkowsky, Nuria et al.

Quelle: Remote Sensing. 16(4)

Schlagwörter: Mapping, Optical properties, Optical remote sensing, Cloud detection, Cloud masks, Cloud optical thickness, Dataset, Earth observations, Machine learning methods, Machine-learning, Multispectral imagery, Synthetic datasets, Thickness estimation, Machine learning

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-72841
https://doi.org/10.3390/rs16040694

CArDIS: A Swedish Historical Handwritten Character and Word Dataset

Autoren: Yavariabdi, Amir Kusetogullari, Hüseyin Celik, Turgay et al.

Quelle: IEEE Access. 10:55338-55349

Schlagwörter: Character recognition, Optical character recognition software, Feature extraction, Hidden Markov models, Handwriting recognition, Machine learning, Image recognition, Character and word recognition, machine learning methods, optical character recognition (OCR), old handwritten style, Swedish handwritten character dataset, Swedish handwritten word dataset

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:bth-23171
https://doi.org/10.1109/ACCESS.2022.3175197

Ability to Borrow Modeling Techniques for Small and Medium-Sized Enterprises

Autoren: Malakauskas, Aidas Lakstutiene, Ausrine Sineviciene, Lina et al.

Quelle: Engineering Economics. 36:516-528

Schlagwörter: the Baltic states, ability to borrow, machine learning methods, SMEs, gradient boosting

Dateibeschreibung: application/pdf

Data-driven assessment of arch vortices in simplified urban flows

Autoren: Martínez Sánchez, Álvaro Lazpita, Eneko Corrochano, Adrián et al.

Quelle: International Journal of Heat and Fluid Flow. 100

Schlagwörter: CFD, Data-driven methods, High-fidelity LES, Machine-learning methods, POD, Urban flow

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-330051
https://doi.org/10.1016/j.ijheatfluidflow.2022.109101

Technical-economic evaluation of a 94.5 MW wind power plant at different elevation heights. A case study in Peru's countryside

Autoren: Priscila Scarlet Portocarrero Mendoza Villicaña Ortiz, Eunice

Weitere Verfasser: Priscila Scarlet Portocarrero Mendoza Villicaña Ortiz, Eunice

Quelle: Journal of Engineering Research. 13:1089-1103

Schlagwörter: Renewable energy, Levelized cost of energy, FOS: Political science, Aerospace Engineering, FOS: Mechanical engineering, Structural engineering, FOS: Law, Wind power in Peru, 7. Clean energy, Environmental science, Elevation (ballistics), Engineering, Meteorology, Artificial Intelligence, 11. Sustainability, Wind farms, FOS: Electrical engineering, electronic engineering, information engineering, Machine Learning Methods for Solar Radiation Forecasting, Electrical and Electronic Engineering, Rural area, Power station, Political science, Wind Power Integration in Power Systems, Geography, 15. Life on land, Economic feasibility, 13. Climate action, Electrical engineering, Physical Sciences, Computer Science, Wind Energy Technology and Aerodynamics, Wind power, Law

Dateibeschreibung: application/pdf

ARDIS: A Swedish Historical Handwritten Digit Dataset

Autoren: Kusetogullari, Hüseyin Yavariabdi, Amir Cheddad, Abbas et al.

Quelle: Neural Computing & Applications. 32(21):16505-16518

Schlagwörter: Handwritten digit recognition, ARDIS dataset, Machine learning methods, Benchmark

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:bth-17741
https://doi.org/10.1007/s00521-019-04163-3

Learning machines in Internet-delivered psychological treatment

Autoren: Boman, Magnus Ben Abdesslem, Fehmi Forsell, Erik et al.

Quelle: Progress in Artificial Intelligence. 8(4):475-485

Schlagwörter: Ensemble learning, Gating network, Internet-based psychological treatment, Learning machine, Machine learning, Decision support systems, Learning systems, Conceptual levels, Decision supports, Learning machines, Machine learning methods, Operational model, Organizational knowledge, Psychological treatments, Patient treatment

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-39062
https://doi.org/10.1007/s13748-019-00192-0

Identification of fungal diseases in strawberry by analysis of hyperspectral images using machine learning methods

Autoren: A. F. Cheshkova

Quelle: Vavilovskii Zhurnal Genet Selektsii
Вавиловский журнал генетики и селекции, Vol 29, Iss 2, Pp 310-319 (2025)

Schlagwörter: hyperspectral imaging, fungal diseases of strawberries, machine learning methods, Genetics, Original Article, QH426-470, dimensionality reduction

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/40264803
https://doaj.org/article/19a0a0327c8f4ddb9a2d419d562cfd58

Econometric advances in causal inference: The machine learning revolution

Autoren: Mallik, Shuvo Kumar Uddin, Imran Trisha, Sadia Maliha et al.

Quelle: GSC Advanced Research and Reviews. 22:229-244

Schlagwörter: Empirical work, Machine Learning Methods, Applied economics, Econometric Literature, Value

Comparative analysis of the Russian regions using machine learning methods for a set of indicators of electronic services

Autoren: L. A. Borisova

Quelle: Цифровая социология, Vol 7, Iss 4, Pp 33-43 (2025)

Schlagwörter: statistics, electronic services, correlation, dendrogram, machine learning methods, regression, Sociology (General), digitalisation, classification of regions, clustering, HM401-1281

Zugangs-URL: https://doaj.org/article/56ca90665e804b9f8a0c2fe50a5074be

THE EMPEROR, HITCHCOCK AND PATRIARCHY: AI-ASSISTED VS. HUMAN GENERATED KEY WORDS EXTRACTED FROM UNPROCESSED ETHNOLOGICAL MATERIAL

Autoren: Ilina Jakimovska Dragan Jakimovski

Quelle: EtnoAntropoZum, Vol 24, Iss 24 (2024)

Schlagwörter: ethnology, unprocessed text, GN301-674, keywords extraction, machine learning methods, Ethnology. Social and cultural anthropology

Zugangs-URL: https://doaj.org/article/a68ac32debce45878991e8172864d27a

Statement of the Problem of Determining the Technical Appearance and Design Characteristics of Multi-Apartment Residential Buildings Based on the Expert Systems Method

Autoren: Alexander A. Merkulov Yury N. Razoumny Olga A. Saltykova et al.

Quelle: RUDN Journal of Engineering Research, Vol 25, Iss 3, Pp 319-329 (2024)

Schlagwörter: engineering concept, machine learning methods, expert systems, structural optimization, fuzzy logic, TA1-2040, technical appearance, Engineering (General). Civil engineering (General), decision support systems

Zugangs-URL: https://doaj.org/article/381e97ea1bb348248e4efde2c29200d8

AI-driven environmental epidemiology: a generalisable framework for predicting blood pressure using fair and explainable machine learning

Autoren: Coffey, Claire Nikolaou, Nikolaos Cea, Donatella et al.

Schlagwörter: Machine Learning methods, Public health policy, Blood pressure, Environmental epidemiology

Zugangs-URL: https://elib.dlr.de/213275/

Theory-guided hard constraint projection (HCP): A knowledge-based data-driven scientific machine learning method

Autoren: Chen, Y. Huang, D. Zhang, D. et al.

Quelle: Journal of Computational Physics. 445

Schlagwörter: Constraint patch, Hard constraint, Physics informed, Projection, Sparse observation, Theory guided, Constrained optimization, Deep learning, Expert systems, Forecasting, Neural networks, Fully connected neural network, Governing equations, Machine learning methods, Machine learning models, Mathematical proof, Physical constraints, Physical principles, Prediction accuracy, Learning systems

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-55827
https://doi.org/10.1016/j.jcp.2021.110624

Predictive modeling for clinical trial completion: assessing the phase success: enhancing trial predictions through uncertainty quantification

Autoren: Rossi, Ginevra Han, Qiwei RUN

Weitere Verfasser: Rossi, Ginevra Han, Qiwei RUN

Schlagwörter: Clinical trials, Health Care, Artificial Intelligence, Machine learning methods, Predictive modeling, Model interpretability, Selective classification, Domínio/Área Científica::Ciências Sociais::Economia e Gestão

Dateibeschreibung: application/pdf

Verfügbarkeit: http://hdl.handle.net/10362/186948

Machine learning prediction of compressional slowness in fractured carbonates: balancing data volume and incremental log features

Autoren: Hamed Aghaei Ghazal Piroozi Salah Mahdi Ressan Al-Maliki et al.

Quelle: Geomechanics and Geophysics for Geo-Energy and Geo-Resources, Vol 11, Iss 1, Pp 1-34 (2025)

Schlagwörter: Compressional slowness (DTC), Machine learning methods, Fractured carbonate formation, Feature data volume and input feature sensitivity, Reservoir characterization, Geophysics. Cosmic physics, QC801-809

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2363-8419; https://doaj.org/toc/2363-8427

Zugangs-URL: https://doaj.org/article/a872301a27f5431ea539a99f7f6e3f6b

Axial strength prediction of FRP reinforced concrete columns under concentric and eccentric loading using machine learning models

Autoren: Mohammad Haji Mohammad Sadegh Marefat Ali Kheyroddin

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-27 (2025)

Schlagwörter: RC Columns, FRP-reinforcement, Eccentricity, Axial strength, Machine learning methods, Medicine, Science

Dateibeschreibung: electronic resource

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

Zugangs-URL: https://doaj.org/article/e6290af4b8004ee7bbd8a6ec9224d933

Comparative evaluation of deep learning and traditional models for predicting traffic accident severity in Saudi Arabia

Autoren: Fayez Alanazi Ibrahim Khalil Umar Ahmed. M. Yosri et al.

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-16 (2025)

Schlagwörter: Machine learning methods, Accident severity, Fatality, Saudi Arabia, Medicine, Science

Dateibeschreibung: electronic resource

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

Zugangs-URL: https://doaj.org/article/29e1a751d97c48e0998fc27287a55a2a

Modeling, Simulation, and Control of a Rotary Inverted Pendulum: A Reinforcement Learning-Based Control Approach

Autoren: Ruben Hernandez Ramon Garcia-Hernandez Francisco Jurado

Quelle: Modelling, Vol 5, Iss 4, Pp 1824-1852 (2024)

Schlagwörter: rotary inverted pendulum, 0209 industrial biotechnology, Engineering design, TA174, machine learning methods, 0202 electrical engineering, electronic engineering, information engineering, modeling, 02 engineering and technology, underactuated mechanical systems, simulation, simulation visualization

Zugangs-URL: https://doaj.org/article/4dc779c51f734b02b154d17072c46481