弱化缓冲算子模型在电视台内设备管理工作中的应用

Application of Weakened Buffering Operator Model in Equipment Management Work in Television Stations

针对电视台设备使用数据存在干扰因素多、传统灰色模型预测效果差的不足,本文利用弱化缓冲算子能够有效处理含有干扰因素的原始数据的优势,较好地改善了基础模型的预测精度。本文选用2种弱化缓冲算子对电视设备使用数据进行预测和模型检验,结果表明,缓冲弱化算子EGM(1,1)模型的预测精度明显高于EGM(1,1)模型和离散灰色预测模型DGM(1,1)。通过对专业电视设备的分析和预测,为电视台设备管理数字化、自动化提供了有效的数据预测模型,具有一定的理论意义和现实意义。

Aiming at the insufficiency of TV equipment using data with many interference factors and poor prediction performance of the traditional grey prediction model,this article utilizes the advantages of weakening buffer operators to effectively process raw data containing interference factors,effectively improving the prediction accuracy of the basic model.In this paper,two kinds of weakening buffer operators are used to forecast and verify TV equipment usage data.The results show that the prediction accuracy of the weakened buffering operator EGM(1,1)model is significantly higher than that traditional DGM(1,1)model and EGM(1,1).By analyzing and predicting professional television equipment,an effective data prediction model has been provided for the digitization and automation of television station equipment management,which has a certain theoretical and practical significance.