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Heating Ventilation and Air Conditioning (HVAC) systems are designed to provide a comfortable indoor thermal environment for the occupants. Conventionally, Predicted Mean Vote (PMV) model is used to represent thermal comfort which is only an average model and it cannot reflect the individual differences in thermal sensation. This paper proposes a personalized thermal comfort model based on a machine...
In view of the influence of smart meter's reliability on smart grid, this paper presents a reliability prediction optimal model of smart meter. Firstly, establish the reliability model of smart meter based on the component stress method. Secondly, combined with the field data, smart meter prediction model is established based on new Weibull distribution parameter method and point estimation method...
Abstract-Dynamic optimization techniques such as dynamic voltage and frequency scaling (DVFS), power gating (PG) and thread migration are widely used in current multi-core processor platforms to boost performance, lower power and improve energy efficiency. To obtain the best optimization results, an important issue is to predict the performance of each thread quantitatively. In this paper, a separated...
Aiming at the disadvantage of system efficiency, a novel control strategy of maximizing energy saving while meeting the cooling demand for vapor compression refrigeration cycle (VCC) is presented. The VCC system is a core element in heating, ventilating, and air-conditioning (HVAC) system, and its coefficient of performance (COP), a measure of system efficiency for VCC system, is strongly influenced...
As well-known, model predictive control is closely related to optimal control. This paper studies relationships between them and provides a unified framework for optimality analysis of model predictive controllers (MPC). The optimality is evaluated by comparing total performance of MPC with finite and infinite horizon optimal cost. Based on relaxed value iteration method, upper and lower bounds of...
Chabagou, a small watershed in Loess Plateau, is a typical area with waterfall and geographic features. The research on the adaptability of different erosion and sediment yield models will be of great importance to the productive practice and the research on erosion and sediment in these areas. The thesis chooses two different types of erosion models (empirical watershed scale model and distributed...
To track the wide range of operating points of fast time-varying processes, a novel multiple model off-line predictive control algorithm is presented. The proposed method is a combination of multiple model strategy and predictive control. Firstly, we locally describe the original nonlinear system around an operating point employing linear time varying (LTV) model. Then the offline model predictive...
With the gradually subsided of economic crisis, China's fast moving consumer goods industry has present slow growth trend. But its market share is still not high. According to the characteristics of China's fast moving consumer goods industry, it is necessary to carry out the strategic transformation at this stage. This article departure from the beer industry, a particular fast moving consumer goods...
Defect number prediction is essential to make a key decision on when to stop testing. For more applicable and accurate prediction, we propose an ensemble prediction model based on stacked generalization (PMoSG), and use it to predict the number of defects detected by third-party black-box testing. Taking the characteristics of black-box defects and causal relationships among factors which influence...
With the development of power industry, the proportion of Large-scale Generating Unit in power grid is getting bigger and bigger. The control object of the generating unit is a complicated manufacturing process which is strong-coupling, time-variable, nonlinear and big-lag. It is difficult to establish accurate model when the parameters of control object is uncertainty because of all disturbances,...
The theories of phase space reconstruction and Support Vector Machines (SVM) are introduced firstly. A novel time series forecasting model based on wavelet and SVM is proposed. It first performances multi-scaled decomposition on complex time series using discrete wavelet transformation. Then the reconstructed approximate series and detail series are forecasted respectively using SVM. Finally, the...
The basic principle of combination forecasting is to give the proper weight combination into a single composite model from the results of each single forecasting model. Therefore, in the process of combination, each single model's advantages strengthened, and disadvantages weaken. Combination forecasting model has higher accuracy and reliability by integrating useful information of each single model...
In popular outlier processing methods, some emphasize on spotted outliers processing and some emphasize on isolated outliers processing. They have seldom processed outliers from the perspective of outlier producing mechanism. This paper aims at the problem of outliers in dam safety monitoring and an outlier identify method which based on BP neural network is presented. This method based on the mechanism...
Type-II fuzzy model is useful to handle the influence of uncertainties. This paper presents an algorithm of Type-II T-S fuzzy (T2TSF) modeling based on data clustering and two approaches to design T2TSF model-based predictive controllers. As the T2TSF model is an extension of T1TSF (Type-I T-S fuzzy) model, the T2TSF modeling algorithm divides the input-output data set into several Type-I fuzzy sets...
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