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Research of combination forecasting mode based on improved analytic hierarchy process

机译:基于改进分析层次过程的组合预测模式研究

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摘要

The weighting method of the traditional fixed combination forecasting model is the only criterion considered to improve accuracy, which has some limitations. In order to improve the comprehensive prediction performance of the combined model, hierarchical structure of the combined model by selecting some parameters which can reflect the performance of the model (including prediction accuracy, robustness, sensitivity, and the amount of fitting data) is established and a kind of multiple factor and multiple criteria weighting method of combination forecasting model is put forward. Based on SVR model, GM (1, 1) model, and ARIMA model, a combination forecasting model based on Improved Analytic Hierarchy Process (AHP) is constructed and applied to a foundation pit. The experimental results show that the combined forecasting model based on improved AHP are better than the single model in precision and robustness; it also has good effect in sensitivity, which has more comprehensive prediction performance than the single models, and has good engineering and practical value.
机译:传统的固定组合预测模型的加权方法是唯一认为提高准确性的标准,这具有一些限制。为了提高组合模型的综合预测性能,通过选择可以反映模型性能的组合模型的层次结构(包括预测精度,鲁棒性,灵敏度和拟合数据量)和提出了一种多个因素和多重标准加权方法。基于SVR模型,GM(1,1)模型和ARIMA模型,构建基于改进的分析层次(AHP)的组合预测模型(AHP),并应​​用于基坑。实验结果表明,基于改进的AHP的组合预测模型优于单一模型精度和鲁棒性;它对敏感性效果良好,具有比单一型号更全面的预测性能,具有良好的工程和实用价值。

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