Výsledky vyhledávání - "Model Performance Metrics"

Predicting design suitability of box-shaped sustainable timber structural members using machine learning and hyperparameter optimization

Autoři: Muhammed Cosut Gebrail Bekdas Sinan Melih Nigdeli a další

Přispěvatelé: Muhammed Cosut Gebrail Bekdas Sinan Melih Nigdeli a další

Zdroj: Neural Computing and Applications. 37:24123-24148

Témata: Hyperparameter Optimization, Box-shaped Member, Support Vector Regression, Timber, Performance Metrices, Learning Systems, Structural Analysis, Machine Learning, Naive Bayes, Timber Structures, Energy Dissipation, Learning Algorithms, Structural Members, Logistic Regression, Machine-learning, Hyper-parameter Optimizations, Model Performance Metric, Decision Trees, Timber Structure, Logistics Regressions, Discriminant Analysis, Modeling Performance, Classification, Structural Optimization, Gaussians, Nearest Neighbor Search, Model Performance Metrics, Forecasting

Predicting Ocean Current Temperature Off the East Coast of America with XGBoost and Random Forest Algorithms Using Rstudio

Autoři: Lulut Alfaris Anas Noor Firdaus Ukta Indra Nyuswantoro a další

Zdroj: Ilmu Kelautan, Vol 29, Iss 2, Pp 273-284 (2024)

Témata: predictive accuracy, QH301-705.5, 13. Climate action, machine learning methods, forecasting, model performance metrics, GC1-1581, 14. Life underwater, Biology (General), Oceanography

Přístupová URL adresa: https://doaj.org/article/2dff3c18e2894c82a08e350767985dcc

Automatic Transformation of natural language requirements to PLCOPen XML using Large Language Models (LLM)

Autoři: Restrepo Torres, Nicolás

Témata: text-to-XML transformation, structured output generation, software automation, PLCopen XML, BLEU score, Electrical Engineering, Electronic Engineering, Information Engineering, clustering methods, software verification, AI for industrial applications, industrial automation, synthetic datasets, NLP4RE, Elektroteknik och elektronik, AI-driven requirements transformation, engineering AI, automated requirements processing, structured data generation, machine learning for requirements engineering, AI-powered software pipelines, model fine-tuning, model performance metrics, Automatic transformation, LLM, function block diagrams, privacy-preserving AI, computational constraints, text-to-code generation, NLP, hybrid AI models, prompt engineering, AI-assisted software engineering, Computer Systems, large language models, natural language processing, AI model evaluation, software design automation, AI-driven software development, ROUGE score, automated software documentation, domain-specific AI, METEOR score, explainability in AI, Datorsystem, semantic analysis, ambiguity resolution, resource-efficient AI, AI in railway industry, RE, requirements engineering, FBD

Popis souboru: application/pdf

Přístupová URL adresa: http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-70073

Artificial neural network model to predict student performance using nonpersonal information

Autoři: Heyul Chavez Bill Chavez-Arias Sebastian Contreras-Rosas a další

Zdroj: e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)
Frontiers in Education, Vol 8 (2023)
UPC-Institucional
Universidad Peruana de Ciencias Aplicadas
instacron:UPC
Frontiers in Education

Témata: Artificial neural network, Artificial intelligence, Effectiveness of Intelligent Tutoring Systems, Class (philosophy), Course pass rate, personal data, Social Sciences, forecasting, privacy, Artificial neural network model, Education, Data from The Open University, Number of course attempts, Model performance metrics, Sociology, Artificial Intelligence, Computer security, Personally identifiable information, Cognitive psychology, Machine learning, Psychology, Student Modeling, L7-991, Educational Data Mining, Informática, Transformative Potential of Blended Learning in Education, Data-driven Education, 4. Education, 05 social sciences, academic performance, Education (General), Intelligent Tutoring Systems, neural networks, Social science, Computer science, Privacy considerations, Mathematics education, Computer Science Applications, FOS: Sociology, FOS: Psychology, Compromise, Use of virtual materials, Computer Science, Physical Sciences, Student Performance Prediction, Recall, Educational Data Mining and Learning Analytics, 0503 education, Student performance forecasting

Popis souboru: application/pdf

Přístupová URL adresa: https://hdl.handle.net/10016/36691
https://doaj.org/article/092584b496294cfea2f02fb4d7940767
http://hdl.handle.net/10757/668167

Search for dark matter in monotop events at the Large Hadron Collider

Pesquisa por matéria escura em eventos monotop no Grande Colisionador de Hadrões

Autoři: Teixeira, Maura Gabriela Barros Castro, Nuno Filipe Romão, Miguel Correia dos Santos Crispim a další

Přispěvatelé: Teixeira, Maura Gabriela Barros Castro, Nuno Filipe Romão, Miguel Correia dos Santos Crispim a další

Zdroj: urn:tid:202638766

Témata: Dark matter, Machine learning, Model performance metrics, Monotop, Aprendizagem automática, Matéria escura, Mètricas

Popis souboru: application/pdf

Dostupnost: https://hdl.handle.net/1822/73681

Analyzing model performance in the presence of synthetic data

Autoři: Martín Peyrona, Alex Ruiz Ordóñez, Magda Mujica Delgado, Luis Eduardo

Přispěvatelé: Martín Peyrona, Alex Ruiz Ordóñez, Magda Mujica Delgado, Luis Eduardo

Zdroj: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)

Témata: Medical Tabular Data, Healthcare, Deep learning, AI and ML Tools, Data Availability, Àrees temàtiques de la UPC::Enginyeria biomèdica, Synthetic Data Generation, Synthetic Data Quality, Predictive Models, Technical Feasibility, Aprenentatge automàtic, Cross Validation, Model Sensitivity, Mortality, Intel·ligència artificial -- Aplicacions a la medicina, Intubation, Model Performance Metrics, Artificial intelligence -- Medical applications

Popis souboru: application/pdf

Přístupová URL adresa: https://hdl.handle.net/2117/419937

Weakening and strengthening structures in the Hadley Circulation change under global warming and implications for cloud response and climate sensitivity

Autoři: Su, Hui Jiang, Jonathan H. Zhai, Chengxing a další

Zdroj: Journal of Geophysical Research: Atmospheres. 119:5787-5805

Témata: the Hadley Circulation, 13. Climate action, cloud feedback, satellite observations, climate sensitivity, model performance metrics, global warming, 01 natural sciences, 0105 earth and related environmental sciences

Přístupová URL adresa: https://agupubs.onlinelibrary.wiley.com/doi/pdfdirect/10.1002/2014JD021642
http://ui.adsabs.harvard.edu/abs/2014JGRD..119.5787S/abstract
https://onlinelibrary.wiley.com/doi/abs/10.1002/2014JD021642
http://doi.wiley.com/10.1002/2014JD021642
https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2014JD021642
http://onlinelibrary.wiley.com/doi/10.1002/2014JD021642/abstract
https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2014JD021642

Analyzing model performance in the presence of synthetic data

Autoři: Universitat Politècnica de Catalunya. Departament de Matemàtiques Ruiz Ordóñez, Magda Mujica Delgado, Luis Eduardo a další

Témata: Àrees temàtiques de la UPC::Enginyeria biomèdica, Artificial intelligence -- Medical applications, Deep learning, Synthetic Data Generation, Predictive Models, Intubation, Mortality, Data Availability, Medical Tabular Data, AI and ML Tools, Healthcare, Technical Feasibility, Synthetic Data Quality, Cross Validation, Model Performance Metrics, Model Sensitivity, Intel·ligència artificial -- Aplicacions a la medicina, Aprenentatge automàtic, Master thesis

URL: https://hdl.handle.net/2117/419937

Implementation of the Automated Numerical Model Performance Metrics System

Autoři: NAVAL RESEARCH LAB STENNIS DETACHMENT STENNIS SPACE CENTER MS OCEANOGRAPHY DIV Dykes, James D

Zdroj: DTIC

Témata: Physical and Dynamic Oceanography, Computer Programming and Software, COMPUTER PROGRAMS, METRICS, OBSERVATION, OCEAN CURRENTS, OCEAN MODELS, PREDICTIONS, TEST AND EVALUATION, ACOUSTIC VELOCITY, AUTOMATION, COMPUTERIZED SIMULATION, FORECASTING, MATCHING, OCEANOGRAPHIC DATA, REAL TIME, SALINITY, SATELLITE IMAGERY, STATISTICAL DATA, TEMPERATURE, NAVY COASTAL OCEAN MODEL, HYBRID COORDINATE OCEAN MODEL, MODEL PERFORMANCE, MODEL PERFORMANCE STATISTICS, AUTOMATED MODEL PERFORMANCE METRICS, AUTOMETRICS SYSTEM, OBSERVATION PROFILES, MODELED PROFILES, SOUND SPEED PROFILES, SOFTWARE MODULES, SEA SURFACE HEIGHT, HINDCASTING, PE0602435N, WUNRL734320015, Text

URL: https://apps.dtic.mil/docs/citations/ADA550135