In this work, we apply for the first time a machine learning approach to design and optimize VO based nanostructured smart window performance. An artificial neural network was trained to find the relationship between VO smart window structural parameters and performance metrics-luminous transmittance (T) and solar modulation (ΔT), calculated by first-principle electromagnetic simulations (FDTD method). Once training was accomplished, the combination of optimal T and ΔT was found by applying classical trust region algorithm on the trained network. The proposed method allows flexibility in definition of the optimization problem and provides clear uncertainty limits for future experimental realizations.
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| http://dx.doi.org/10.1364/OE.27.0A1030 | DOI Listing |
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