Abstract
This study first created a model to predict the content of free calcium oxide (fCaO) of the calcined clinker in the rotary kiln by adopting the technologies of rough sets, neural networks and data fusion. And then it was used to predict the quality of the calcined clinker in the rotary kiln and pleasant simulation results were obtained, indicating that the model is valid and has attained the goal of increasing the training speed and precision. Besides, it has solved many problems in the course of cement production, such as big inertia, lagging, time variation, serious nonlinearity, multiple parameters, serious coupling, and difficulty in creating systematic models.KeywordsData FusionDecision TableDecision AttributeRotary KilnCement ProductionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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