This repo demonstrates how to build a surrogate (proxy) model by multivariate regressing building energy consumption data (univariate and multivariate) and use (1) Bayesian framework, (2) Pyomo package, (3) Genetic algorithm with local search, and (4) Pymoo package to find optimum design parameters and minimum energy consumption.
machine-learning-algorithms cross-validation multi-objective-optimization pyomo deterministic bayesian-optimization hvac nonlinear-optimization nsga-ii multivariate-regression stochastic-optimization ipopt probabilistic-inference genetic-optimization-algorithm latin-hypercube-sampling building-energy xgboost-regression sobol-indices gurobi-solver pymoo
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Updated
Mar 15, 2023 - Jupyter Notebook