基于灰色关联度分析的垃圾与棉杆混燃过程建模

doi:10.3969/j.issn.1000-7229.2015.02.021

摘要/Abstract

摘要：

为实现对垃圾与棉杆混燃过程中各运行条件的优化调整，首先需要提供准确的混燃过程模型，而将所有因素等同地作为模型输入，显然会增加模型的复杂度和计算运行时间，影响模型精度。针对该问题，结合实例，通过数据预处理和灰色关联度分析，确定各影响因素的权重系数，建立了垃圾与棉杆混燃过程最小二乘支持向量机模型。结果表明，与单纯最小二乘支持向量机模型相比，该模型具有更好的拟合效果和泛化能力，有效地提高了垃圾与棉杆混燃过程模型的准确性和稳定性。为实现对垃圾与棉杆混燃过程中各运行条件的优化调整，首先需要提供准确的混燃过程模型，而将所有因素等同地作为模型输入，显然会增加模型的复杂度和计算运行时间，影响模型精度。针对该问题，结合实例，通过数据预处理和灰色关联度分析，确定各影响因素的权重系数，建立了垃圾与棉杆混燃过程最小二乘支持向量机模型。结果表明，与单纯最小二乘支持向量机模型相比，该模型具有更好的拟合效果和泛化能力，有效地提高了垃圾与棉杆混燃过程模型的准确性和稳定性。

关键词: 垃圾与棉杆混燃, 数据预处理, 灰色关联度, 混燃过程模型

Abstract:

To achieve optimal adjustment for various operating conditions of the co-combustion process of waste and cotton stalks, an accurate model of the co-combustion is needed. But if all the factors are equally used as model inputs, the complexity and computation run time of the model will be increased, so the accuracy will be impacted. To solve this problem, combined with examples, through data preprocessing and gray correlation analysis the weight coefficient of each factor was determined, and a least square support vector machine model was established for the waste and cotton stalks co-combustion process. The results show that this model has better fitting result and generalization ability compared with the simple least square support vector machine model, which can effectively improve the accuracy and stability of the co-combustion process model of waste and cotton stalks.

Key words: waste and cotton stalks co-combustion, data preprocessing, gray correlation, co-combustion process model

李大中，唐影. 基于灰色关联度分析的垃圾与棉杆混燃过程建模[J]. 电力建设, 2015, 36(2): 126-130.

LI Dazhong, TANG Ying. Co-Combustion Process Modeling for Waste and Cotton Stalks Based on Gray Correlation Analysis[J]. ELECTRIC POWER CONSTRUCTION, 2015, 36(2): 126-130.

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