Least Squares Support Vector Machine Classifiers
Neural Processing Letters
Optimal control by least squares support vector machines
Neural Networks
Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models
Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models
Support Vector Machines: Theory and Applications (Studies in Fuzziness and Soft Computing)
Support Vector Machines: Theory and Applications (Studies in Fuzziness and Soft Computing)
Intelligent RFID tag detection using support vector machine
IEEE Transactions on Wireless Communications
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Medicine analysis becomes more and more important in our production and life, especially the composition analysis for medicines. Available data are characterized by small amount and high dimensionality. Support vector machine (SVM) is an ideal algorithm for dealing with this kind of data. This paper presents a combined method of principal component analysis (PCA) and least square support vector machine (LS-SVM) to deal with the work of medicine composition analyses. The proposed method is applied to practical problems. Experiments demonstrate the predominance of the proposed method on both running time and prediction precision.