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Accurate classification methods are critical in computer-aided diagnosis and other clinical decision support systems. Previous research has studied methods for combining genetic algorithms for feature selection with ensemble classifier systems in an effort to increase classification accuracy. We propose a two-step approach that first uses genetic algorithms to reduce the number of features used to...
In image annotation system, performance is highly desired. We use a bi-coded chromosome-based genetic algorithm to optimize the weights of multimedia content description interface (MPEG-7) feature descriptors and select optimal feature descriptor subset simultaneously. Two genetic codes are used: a real code represents the weights corresponding to MPEG-7 descriptors; a binary one denotes the presence...
This paper proposed an algorithm of feature selection used in fusion of soft computing and based on the chain of data-information-cognition. The algorithm is as follow: Firstly, the weights wij from input layer to hidden layer are obtained when the training accuracy of BP neural network (BPNN) is got. Where i denotes the i th feature and j denotes the j th node in hidden layer of BPNN. Secondly, zeta...
Power quality events may result in interruption or malfunctioning of electrical equipments that are fed through the voltage line. Detection of such cases by monitoring the voltage waveform remains an important engineering problem. Pattern recognition and classification methods are used for both detection and classification of such events. Although several feature construction and detection/classification...
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