Advances in kernel methods: support vector learning
Advances in kernel methods: support vector learning
Optimal control by least squares support vector machines
Neural Networks
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Realizes the flotation process cleaned coal ash soft Sensor is the key of flotation process automation. First introduction to least square support vector machines algorithm, subsidiary variable choice research on flotation process cleaned coal ash soft sensor is carried out, reasonable subsidiary variable is selected by experiment, soft sensor accuracy of coal change is proposed, experiment show that model accuracy is sensitive for coal change. This soft sensor model is help to flotation process automatic control.