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

机译:基于改进多元线性回归算法的水泥制造功耗预测建模

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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.
机译:本文应用了主成分分析(PCA),因为多种因素影响的水泥制造的现有功耗预测模型非常复杂,精度低。以这种方式,获得了影响水泥制造的功耗的四个新的关键因素,而不是11个原始的重音,其简化了计算模型的复杂性。基于改进多元线性回归算法的水泥制造的功耗预测模型。然后该模型的效率明显改善了预测精度,在平邑中莲水泥厂验证。换句话说,本文提供了水泥厂功耗预测管理的理论基础。

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