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The missing data classification problem is one of the common problems in machine learning. Conventional method eliminates the samples with missing values. In this paper, matrix completion, as a new method is proposed for filling the missing data. And this method and two traditional methods, eliminating the samples with missing values and filling the missing data based on the sample similarity, are...
Some statistical and machine learning methods have been proposed to build hard drive prediction models based on the SMART attributes, and have achieved good prediction performance. However, these models were not evaluated in the way as they are used in real-world data centers. Moreover, the hard drives deteriorate gradually, but these models can not describe this gradual change precisely. This paper...
In this paper, mathematical model for heat treatment is constructed according to the process requirement of Roller-hearth Normalizing Furnace. Based on the intelligent control theory of neural network and particle swarm algorithms, the improved PSO-ANN model is established and simulated using lots of data acquired from the site. The result indicates the improved PSO-ANN model can raise the precision...
This paper analyzed some existing problems of the present air-cargo forecast methods. Then it established the SVM (support vector machine) model for air-cargo demand forecasting. Taking the historical statistical data of Beijing to Shanghai cargo volumes from Jan-2005 to Mar-2006 as fitting and forecasting specimens, we can obtain the prediction model to optimize, which was compared with that of Brown...
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