Surrogate · HVAC & Buildings
Gaussian Process Regression for HVAC & Buildings
Apply the gaussian process regression to real hvac & buildings problems — in the browser, with AI assistance.
GPs model outputs as draws from a distribution over functions, giving both predictions and calibrated uncertainty for expensive simulations.
In hvac & buildings, teams face challenges like thermal comfort, energy efficiency, air quality. The gaussian process regression directly supports use cases such as room airflow cfd, building energy modeling, duct design, and PolySim's AI Copilot can recommend settings and catch common setup errors before you run.
Typical HVAC & Buildings use cases
- Room airflow CFD
- Building energy modeling
- Duct design
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