By Frédéric Magoules, Hai-Xiang Zhao
Concentrating on updated synthetic intelligence types to unravel construction power difficulties, Artificial Intelligence for construction power Analysis studies lately constructed versions for fixing those matters, together with special and simplified engineering tools, statistical tools, and synthetic intelligence equipment. The textual content additionally simulates strength intake profiles for unmarried and a number of constructions. in keeping with those datasets, aid Vector computing device (SVM) versions are proficient and demonstrated to do the prediction. compatible for beginner, intermediate, and complex readers, this can be a important source for development designers, engineers, and scholars
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Additional info for Data Mining and Machine Learning in Building Energy Analysis: Towards High Performance Computing
This mode is suited for pattern classiﬁcation. The advantage of a back-propagation learning algorithm is that it is simple to implement and computationally efﬁcient due to the fact that its complexity is linear in the synaptic weights of the network. However, a major limitation of this algorithm is that the convergence is not always guaranteed and can be excruciatingly slow, particularly when the network topology is large. There are many ways that feed forward neural networks can be constructed.
They found that general regression neural networks and SVMs were more applicable to this problem compared to other models. Furthermore, SVM showed the best performance among all prediction models. The models were trained on the data of 59 buildings and tested on nine buildings. Liang and Du [LIA 07] presented a cost-effective fault detection and diagnosis method for HVAC systems by combining the physical model and a SVM. By using a four-layer SVM classiﬁer, the normal condition and three possible faults can be recognized quickly and accurately with a small number of training samples.
Energy auditing evaluates the efﬁciency of all building components and systems that impact energy use. The audit process begins at the utility meters where the sources of energy coming into a building or facility are measured. Energy ﬂow inputs and outputs for each fuel are then identiﬁed. These ﬂows are measured and quantiﬁed into distinct functions or speciﬁc uses, then the function and performance of all building components and systems are evaluated. The efﬁciency of each of the functions is assessed, and energy and cost-saving opportunities are identiﬁed.