摘要
针对传统的加权组合预测模型赋权过程中的缺陷,分析了诱导有序加权平均算子(IOWA)的特点,建立了一种基于诱导有序加权平均算子的GM(1,1)-Verhulst组合预测模型。结合某矿山沉降实测数据进行基于IOWA算子的组合预测,结果表明基于IOWA算子的组合预测模型预测中误差优于传统的加权几何平均组合模型,更优于单项模型预测精度,预测结果能够很好地反映其沉降趋势。
Aiming at the defects of the traditional weighted combination forecasting method,the characteristics of the induced ordered weighted averaging operator （IOWA） was analyzed, and a GM （I,I） -Verhulst combination prediction model based on the induced ordered weighted averaging operator was established. The verification was carried out through the measured data of a mine settlement. The results show that the combination forecasting model based on IOWA operator, the error was better than the single model prediction accuracy and weight geometric average combination forecast model. The prediction results can well reflect the settlement trend.
作者
赵亚红
王金星
张丽华
ZHAO Ya-hong;WANG Jin-xing;ZHANG Li-hua(Architectural Engineering College, North China Institute of Science and Technology,Beijing 101601 ,China;Beijing Digsur Science and Technology Co., Ltd., Beijing 100012 ,China)
出处
《煤炭技术》
CAS
2018年第7期101-103,共3页
Coal Technology
基金
国家自然科学基金(51178185)
廊坊市科技支撑计划(2016011014)
