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Soft-Sensor Method Based on Least Square Support Vector Machines Within Bayesian Evidence Framework

Soft-Sensor Method Based on Least Square Support Vector Machines Within Bayesian Evidence Framework,10.1007/978-3-540-72395-0_67,Wei Wang,Tianmiao Wan

Soft-Sensor Method Based on Least Square Support Vector Machines Within Bayesian Evidence Framework   (Citations: 1)
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Based on the character and requirement of the dynamic weighing of loader, the soft sensor technique was adapted as the weighing method, and the least square support vector machine (LS-SVM) as its modelling method. Also the Bayesian evidence framework was used in LS-SVM for selecting and tuning its parameter. And then, after the nonlinear regression algorithms of LS-SVM and the principle of Bayesian evidence framework were introduced, the soft sensor model based on LS-SVM was given. In the end, emulation analysis results indicate that soft-sensor method based on LS-SVM within Bayesian evidence framework is a valid means for solving dynamic weighing of loader.
Conference: International Symposium on Neural Networks - ISNN , pp. 535-544, 2007
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