![]() It is always a good idea to use LHS over FFD for a given number of treatments, since the existence of nonlinearity in the relation is not pre-existing information. LHS showed better prediction accuracy compared to FFD, since LHS considers the nonlinear impacts for a given number of treatments. There is an elegant combination of light, sound, and wireless charging that streamlines. For the considered ranges of design parameters, window insulation (WDI) and Solar Heat Gain Coefficient (SHGC) were found to have nonlinear characteristics on cooling and heating loads. With that said, we still believe in the HyperCube Ultimate vision. ![]() The accuracy of predicting the heating/cooling loads of the meta-models for alternative floor designs was compared. ![]() Building energy loads of an office floor with ten design parameters were selected as the meta-models’ objectives, and were developed using the two sampling methods. It connects between the USB charger and your iPhone/Android smartphone, and with a free app, allows you to automatically backup all your photos, videos, and contacts onto a micro SD card or USB drive while you charge your device. In this study, Latin Hypercube Sampling (LHS) is proposed as an alternative to Fractional Factor Design (FFD), since it can improve the accuracy while including the nonlinear effect of design parameters with a smaller size of data. The HyperCube is a tiny device that features a micro SD card slot, a male USB connector and two female USB ports. Generally, it requires many simulated or measured results to build meta-models, which significantly affects their accuracy. Interest in research analyzing and predicting energy loads and consumption in the early stages of building design using meta-models has constantly increased in recent years.
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