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It is important to have practical methods for constructing a good mathematical model for a building's thermal system for energy audits, retrofit analysis and advanced building controls, e.g. model predictive control. Identification approaches based on semi-physical model structures are popular in building science for those purposes. However conventional gray box identification approaches applied to...
Poorly designed excitation signals could lead to inaccurate or, even worse, highly correlated parameter estimates in a data-driven model, so it is critical to have an informative training data set in order to obtain an accurate model in a cost effective manner. This paper investigates a sequential optimal design of experiments (DOE) approach to generate an optimal training data set for varying zone...
There have been very few advanced control algorithms developed for small commercial buildings due to practical difficulties such as the spatial comfort variations, significant disturbances, high sensor costs, and high cost of site-specific engineering solutions. High implementation cost has been a major impediment to successful market penetration. The focus of this work is to develop and demonstrate...
For the feature selection and parameter optimization of LS-SVM, propose a At first, a population of particles (feature subsets) was randomly generated, then the features and parameters are optimized by PSO algorithm. The experiments on the UCI database indicate that the proposed method can efficiently find the suitable feature subsets and LS-SVM parameters. Also, comparison are made against GALS-SVM...
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