Papers by Keyword: Gray Prediction Model

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Authors: You Liang Chen, Lin Li
Abstract: The gray prediction theory has already been widely applied to solving all kinds of social, scientific and technical problems. It is also used for the prediction of engineering mechanical and material scientific problems. But the traditional gray prediction model is applicable only for equidistant time sequences. In order to extend the scope of application, an improved gray prediction model is put forward. By weighted summation, the new developed gray prediction model can also be applied to the situation of non-equidistant time sequence. The improved gray prediction model is used for the prediction of creep fracture time of rocks and gypsum. The deduced results are proven to be very accurate. The research work of the current paper opens many opportunities for further thoughts of the prediction of many other engineering mechanical problems.
Authors: Hui Juan Zhang, Yan Ting Wang, Shi Tao Wang, Meng Wu
Abstract: The paper introduces a new method for prediction of electromagnetic compatibility in the power system, and use the Electromagnetic simulation software ATP. By comparing the actual test results to the simulation results, it is proved that electromagnetic transient simulation is reliable and effective. It also introduces the Gray prediction theory to predict the next Electromagnetic Interference (EMI) of the substation. It is high practical to research and analyze the substation electromagnetic compatibility, and feasible to use the Gray prediction theory with multivariable for the model EMI prediction analysis.
Authors: Chang Liu
Abstract: This paper studies the problem of load forecast in electric companies. We combine the analysis of load cause and gray prediction model together, and enhance the accuracy of prediction, thus improving the economic benefit of electric companies and saving energy resources. Firstly, considering the cause of load, we separate load into three components: basic load component, weather-sensitive load component, and load component because of special events. Then, we take economic development and actual temperature into account to calculate load in each category. And then, we use gray prediction model to make a further prediction. The results show that gray prediction is only accurate in trend. In order to make a more accurate prediction, it should be combined with other forecasting methods. Finally, we combine cause of load with gray prediction model, and establish a combination forecasting model. The combination forecasting model explains the cause of load and the reason for error in gray model. With accurate forecast, it is easy for electric companies to manage their operation perfectly and get the most profit.
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