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Mechanical and electrical equipments are widely used in industry. Existing electro-hydraulic mixing equipments mainly use expert systems for fault diagnasis. However, in order to increase the accuracy of diagnasis, the expert systems have to acquire more knowledge. And diagnosis system will bring great uncertainty due to limited knowledge. Furthermore, existing fault diagnosis system has the disadvantages...
With the rapid development and popularity of the Internet technology, more and more people like to share their feelings and experiences on the Internet. The increasing rich in network resources, such as personal blogs, online reviews, etc., provide us with new opportunities and challenges. Opinion mining is talking about how to use information technology to mining, and understand the views of others...
Recently, the research on Brain-Computer Interface (BCI) technology has achieved great progress, and the BCI system based on Motor Imagery (MI) has been intensively studied in many labs. The essential part of signal processing in BCI is how to extract the MI features in electroencephalographic (EEG) and recognize the MI task accurately. One challenge lies in that EEG signals are non-stationary, whose...
The application of association rule mining to classification has led to a new family of classifiers which are often referred to as Associative Classifiers (ACs). An advantage of ACs is that they are rule-based and thus lend themselves to an easier interpretation. However, it is common knowledge that association rule mining typically yields a sheer number of rules defeating the purpose of a human readable...
The application of association rule mining to classification has led to a new family of classifiers which are often referred to as associative classifiers (ACs). An advantage of ACs is that they are rule-based and thus lend themselves to an easier interpretation. However, it is common knowledge that association rule mining typically yields a sheer number of rules defeating the purpose of a human readable...
This paper proposes a new email classification model using a linear neural network trained by perceptron learning algorithm (PLA) and a nonlinear neural network trained by back propagation neural network (BPNN). A semantic feature space (SFS) method has been introduced in this classification model. The bag of word based email classification system has the problems of large number of features and ambiguity...
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