Soft-sensing of Steam Dryness Based on ABC-LSSVM Measurement Model
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In order to improve the accuracy of measuring steam dryness,a least squares support vector machine(LSSVM) model optimized with artificial bee colony(ABC)algorithm was proposed,in which,having ABC algorithm used to optimize LSSVM's parameters,and then having the improved LSSVM model employed to measure steam dryness.The soft-sensing results show that the improved LSSVM can meet accuracy requirements;and having both LSSVM and BP neural network measurement model applied to steam dryness measurement proves high efficiency and stability of ABC-LSSVM soft measurement model.