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Despite of good theoretic foundations and high classification accuracy of support vector machines (SVM), normal SVM is not suitable for classification of large data sets, because the training complexity of SVM is very high. This paper presents a novel SVM classification approach for large data sets by considering models of classes distribution (MCD). A first stage uses SVM classification in order...
In the traditional method of flatness pattern recognition known as neural network with a changing topological configuration, slow convergence and local minimum were observed. Moreover, the process of experimenting the initial parameters and structure of the neural network according to the experience before has been proved time-consuming and complex. In this paper, a new approach was proposed based...
A new simple method for identification of GPI-(like)-anchored proteins at sequence level is proposed in this paper. As a binary classifier of GPI-(like)-anchored proteins and non GPI-(like)-anchored proteins, a supervised machine learning algorithm, support vector machine (SVM) and simple representation of C-terminus of protein primary sequences with mean hydrophobicity were used. Not merely does...
Water level is an important index to ensure the safety and stable operation of the ship boiler. Because of the nonlinear and time lag of the water level system, normal PID control can't obtain the satisfactory effect. So the improved neural network predictive control based on support vector machine (SVM) was presented. This method used SVM to identify the predictive model of the system, and used BP...
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