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The cluster combines mathematical modeling, numerical simulation, and learning-based methods into an integrated competency area for analyzing and forecasting complex systems.
Defines scope and boundaries for learning components within modeling and simulation. Included are datasets, preprocessing, feature engineering, training pipelines, learning algorithms, hyperparameter settings, evaluation metrics, experiment logs, reproducibility requirements, model storage formats and evaluation data splits. Excluded are production deployment, operational monitoring, CI/CD pipelines, infrastructure specifications, data security policies and release management.
An organizational concept that goes beyond symptom-level fixes by questioning underlying assumptions and governing rules, enabling systemic improvement and sustained learning.
An approach by which organizations systematically create, share and use knowledge to increase adaptability and performance.