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| Soft Sensor Modeling Based on CSSE-OSELM Algorithm and Its Industrial Application |
| LI Rong-yu,QI Gui-hong |
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Abstract According to the characteristics of soft sensor modeling samples,a soft sensor modeling method called cuckoo search selective ensemble of online sequential extreme learning machine(CSSE-OSELM) is proposed.First of all, OSELM individuals were assembled into the framework of integrated learning,and each OSELM individual is endowed with weight and threshold.Then,with the aid of the cuckoo search algorithm,choose out OSELM individuals,which satisfy the threshold condition ,to a subset of the combined into integrated learning.Finally soft sensor model is established with the subset, with integrating learning and weighted processing.Using UCI standard data sets to test, at the same time, the jet fuel for hydrocracking reaction distillation tower is verified, the simulation results show that the algorithm is superior to the traditional method, with higher prediction precision and stable performance.
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Received: 08 September 2016
Published: 11 August 2017
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2017, Vol. 38 
