Pages that link to "Item:Q2309389"

The following pages link to A machine-learning framework for rapid adaptive digital-twin based fire-propagation simulation in complex environments (Q2309389):

Displaying 19 items.

• A digital twin framework for machine learning optimization of aerial fire fighting and pilot safety (Q2020726) (← links)
• Machine-learning and digital-twins for rapid evaluation and design of injected vaccine immune-system responses (Q2083207) (← links)
• A note on rapid genetic calibration of artificial neural networks (Q2086037) (← links)
• An adaptive digital framework for energy management of complex multi-device systems (Q2086044) (← links)
• A digital-twin and machine-learning framework for precise heat and energy management of data-centers (Q2150249) (← links)
• Modeling and simulation of the infection zone from a cough (Q2221722) (← links)
• A virtual model architecture for engineering structures with twin extended support vector regression (T-X-SVR) method (Q2246326) (← links)
• A digital-twin and machine-learning framework for the design of multiobjective agrophotovoltaic solar farms (Q2666101) (← links)
• A machine-learning framework for the simulation of nuclear deflection of planet-killer-asteroids (Q2679291) (← links)
• Machine-learning a perfect bending soccer goal shot (Q6096495) (← links)
• A machine-learning digital-twin for rapid large-scale solar-thermal energy system design (Q6097615) (← links)
• Locally assembled stiffness matrix: a novel method to obtain global stiffness matrix (Q6098676) (← links)
• Rapid machine-learning enabled design and control of precise next-generation cryogenic surgery in dermatology (Q6147001) (← links)
• Fast heat transfer simulation for laser powder bed fusion (Q6155688) (← links)
• A super-real-time three-dimension computing method of digital twins in space nuclear power (Q6194214) (← links)
• A voxel-based machine-learning framework for thermo-fluidic identification of unknown objects (Q6201159) (← links)
• A digital-twin and rapid optimization framework for optical design of indoor farming systems (Q6584858) (← links)
• A machine-learning enabled digital-twin framework for next generation precision agriculture and forestry (Q6609758) (← links)
• A digital-twin for rapid simulation of modular direct air capture systems (Q6610465) (← links)