The accuracy of most "passive" detection methods for pipeline fault detection depends on the amount of energy generated by the defect point ***,it is difficult to deploy the idea of passive detection on func...
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The accuracy of most "passive" detection methods for pipeline fault detection depends on the amount of energy generated by the defect point ***,it is difficult to deploy the idea of passive detection on functional defects such as blockages,which have a long development period and lack obvious external "warnings".In practice,the pipeline operating conditions are complex with various external interference,as well as little prior knowledge of the subject to be tested can bring great challenges to the detection *** address the above problems,this paper proposes a pipeline blockage detection method using numerical simulation based on low-frequency active acoustic excitation,the manner of calculation of the plane wave cutoff frequency of a known fluid medium in the pipe is studied,so that the plane wave can be generated in an effective frequency range for valid blockage *** simulation results have shown that the proposed method can accurately locate blockages in the pipe with different fluid *** relationship between the amplitude of reflected sound pressure and the size of the blockage is analyzed,and a regression forecasting model is developed using energy entropy as a feature to estimate the blocking degree which is defined by the ratio between the cross-sectional areas of blockage and the *** method is also proved to be able to localize multiple blockages in the pipe accurately.
In this paper, non-linear support vector regression and minimum penalty coefficient K-fold cross validation are described, and then a forecastingmodel of railway freight volume is buit by using these methods. Taking ...
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In this paper, non-linear support vector regression and minimum penalty coefficient K-fold cross validation are described, and then a forecastingmodel of railway freight volume is buit by using these methods. Taking the data of railway monthly freight volume and related factors of our country from Jan 2005 to Nov 2013 as the training samples, this paper regresses and predicts the railway monthly freight volume. The result of regressionmodel shows that this method has high accuracy in the forecast of railway monthly freight volume.
The combination of prediction method is the hottest one of the topics in forecasting *** basic meaning of the combination forecast is the prediction model using the weighted average combinations of two or more for a *...
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The combination of prediction method is the hottest one of the topics in forecasting *** basic meaning of the combination forecast is the prediction model using the weighted average combinations of two or more for a *** forecast of the key is to determine the combination coefficients or weighting *** paper introduces combining forecasting method of water consumption discharge from history data of the past seven *** paper establish the mathematical model of water consumption from multiple perspectives: regression forecasting model, seasonal forecastingmodels, gray forecasting GM(1,1) model and combining forecasting *** forecasts produces better accuracy than any one of the single *** forecast provides important general guidance to short-term and long-term plan of water *** w ell as, with its robustness and accuracy, the optimized compound forecast model is extensible in the forecast o fconsumption of other resources.
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