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In this paper, we propose an intelligent data-analysis method for modeling and prediction of daily electricity consumption in buildings. The objective is to enable a building-management system to be used for forecasting and detection of abnormal energy use. First, an outlier-detection method is proposed to identify abnormally high or low energy use in a building. Then a canonical variate analysis...
Schema-free query processing has become a key technique of XML query for the absence of structural information or over multiple data sources. It is an important issue to effectively and efficiently filter out correct results from many meaningless results. To solve the basic problem of what are meaningful results, we propose a structure-based model for meaningful result determination. This model covers...
Artificial Neural Networks (ANNs) have been applied to machine condition monitoring. This paper first addresses a ANN trained by Group Search Optimizer (GSO), which is a novel population based optimization algorithm inspired by animal social foraging behaviour. The global search performance of GSO has been proven to be competitive to other evolutionary algorithms, such as Genetic Algorithms (GAs)...
The physical mechanism of three-tank water level system is analyzed, and an approximated linear model is deduced to represent the dynamic property of the water level system around an equilibrium point. On the other hand, Three different identification methods based on different model structures: linear model, BP neural network model, nonlinear Hammerstein ARMAX model are used to identify the dynamical...
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