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When a large number of service requests, the matching algorithm of semantic-based web service appear the shortcomings of inefficient. A new matching algorithm based on the cache library is proposed. The service which matched successfully at first was put into the cache library. When the service requested come, it should first match with the service in the cache library, if fails then match with the...
In this paper, a clustering method for handwritten digit recognition is studied. The digit samples, firstly are processed and features are extracted. Based on these features, a clustering method is designed and implemented to cluster the digit samples. Experiments finally show that the clustering method is efficient in handwritten digit recognition.
Support vector machine (SVM) is discussed to use for recognizing cucumber leaf diseases in this paper. Considering that it is a small number of samples, a new experimental program has been proposed which takes each spot of leaves as a sample instead of taking each leaf as a sample. In the experiments Radial Basis Function (RBF), polynomial and Sigmoid kernel function were also used to carry out comparative...
Audio classification is an important preprocess to the audio data. However, lots of manual labeled data are needed for training models. In order to solve this problem, we evaluate a semi-supervised machine learning algorithm called co-training for content-based audio classification. The audio is divided into there classes: pure speech, pure music and speech mixed with music. We consider the audio...
This paper aims at the BP neural network model, to against the problems of the weakness of capability of knowledge acquisition and low stability of learning and memory. The paper put forward a new fast error back propagation algorithm, and give an example to make a comparison between BP algorithm and FBP algorithm on fault diagnosis, The diagnosis results indicate the reliability of this method.
A fault diagnosis method for analog circuits based on Support Vector Machine (SVM) and AdaBoost algorithm is developed in this paper. Firstly, output voltage signals from the test nodes are obtained from analog circuits test points and the fault feature vectors are extracted from Haar wavelet packet transform coefficients. Then, after training the AdaBoost SVM by faulty feature vectors, the SVM ensemble...
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