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4 days agoExamples of learning algorithms used in predicting building performance (e.g., energy use, thermal comfort, GHG emissions, cost, etc. ) include ANN [14], [16], ...
3 days agoRadian scaling substantially shortens the training time taken to train the forecasting models compared with the models that use previous normalization methods.
16 hours agoShort-term measurements are then used to create a chiller load model that predicts the year-round variation of the facility's load. Conducting M&V for a chiller ...
7 days agoThis review aims to serve as a comprehensive resource for researchers interested in understanding the current landscape of quantum algorithms for linear systems ...
6 days agoA piecewise polynomial constructs the load trajectory in a low-dimensional flat space, which is then mapped to a high-dimensional generalized state space ...
2 days agoWe develop a framework for learning properties of quantum states beyond the assumption of independent and identically distributed (i.i.d.) input states.
4 days agoWe study a general class of nonlinear iterative algorithms which includes power iteration, belief propagation and approximate message passing, ...
5 days agoThis study employed machine learning algorithms to train DH parameters derived from the IAPWS-95 method. It could establish empirical formulas for DH ...
3 days agoApplying multiple algorithms for building envelope optimization. Applying a meta-model approach to avoid the repeating simulation cases.
4 days agoPrecipitation during a specific return period plays an important role in the design of hydraulic infrastructure. The traditional approach involves ...