Add time:08/18/2019         Source:sciencedirect.com

A self-tuning multi variable predictor algorithm which is capable of providing multi step prediction of a multi variable stochastic time series is presented and applied to the problem of predicting the quality of sinter produced by an iron ore sintering process. Predicted information on strength index and FeO content of the sinter product is obtained from present and past measurements of these quantities together with coke-rate and a temperature-speed factor. The study includes the use of an extended low-pass filtering technique which produces a smaller time-lag than conventional low-pass filters. The predicted information may be used by the plant operator to effect better control of the end-product.

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