Power Consumption Prediction Modeling of Cement Manufacturing Based on the Improved Multiple Non-Linear Regression Algorithm

Abstract:

The principal component analysis (PCA) is applied in this paper, since the existing power consumption prediction models of cement manufacturing influenced by many factors are quite complex and have low accuracy. In this way, four new key factors affecting the power consumption of cement manufacturing are obtained instead of the eleven original ones, with the complexity of the computing model simplified. Built upon this is the power consumption prediction model of cement manufacturing based on an improved multiple non-linear regression algorithm. Then the efficiency of the model, obviously improved the forecasting precision, is verified in Pingyi Zhonglian Cement Plant. In other words, a theoretical basis for cement plants power consumption forecasting management is provided in this paper.

• Periodical: Applied Mechanics and Materials (Volumes 687-691)
• Pages: 5185-5189
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.687-691.5185
• Online since: November 2014
• Authors: Hui Zhao*, Ning Zhang, Hong Jun Wang
• Keywords: Cement Manufacturing, Multiple Non-Linear Regression, Power Consumption Prediction, Principal Component Analysis (PCA)

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