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To overcome the difficulty that silicon content in hot metal can not be effectively controlled in ironmaking process due to lack of real-time on-line instrumentation, a prediction method is proposed by combining the Kernel Principal Component Analysis(KPCA) with the Least Square Support Vector Machine(LSSVM). Using KPCA as a preprocessor of LSSVM to extract the principal features of original data...
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