Abstract
The flotation process refined coal ash soft measuring is the key technology to the flotation process automation .Based on the generalized regression RBF neural network and the introduction of least squares support vector machines (SVM) algorithm ,by BP, RBF, generalized regression RBF and least squares support vector machine flotation refined coal ash soft measuring modeling comparison, in the circumstances of using small sample ,the model accuracy and generalization ability of the least squares support vector machine (SVM) which is based on statistics theory of learning can be well verified. It provide the reliable basis for the flotation process refined coal ash soft survey modeling which used the least squares support vector machines.
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Wang, R. (2011). Neural Network and Support Vector Machines in Slime Flotation Soft Sensor Modeling Simulation Research. In: Deng, H., Miao, D., Wang, F.L., Lei, J. (eds) Emerging Research in Artificial Intelligence and Computational Intelligence. AICI 2011. Communications in Computer and Information Science, vol 237. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24282-3_70
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DOI: https://doi.org/10.1007/978-3-642-24282-3_70
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