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This paper presents a novel hybrid approach to outlier detection by incorporating local data uncertainty into the construction of a global classifier. To deal with local data uncertainty, we introduce a confidence value to each data example in the training data, which measures the strength of the corresponding class label. Our proposed method works in two steps. Firstly, we generate a pseudo training...
The Venturi flow meters that are being used to measure the feedwater flow rate in most pressurized water reactors are confronted with fouling phenomena, resulting in an overestimation of the flow rate. In this paper, we will therefore develop two soft-sensing models based on a fuzzy inference system and support vector regression for online prediction of the feedwater flow rate. The data-based models...
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