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作 者:王路平 卢占会[1] 魏鑫 方明[3] 王祥科[3] WANG Luping;LU Zhanhui;WEI Xin;FANG Ming;WANG Xiangke(School of Mathematics and Physics,North China Electric Power University,Beijing 102206,China;College of Control and Computer Engineering,North China Electric Power University,Beijing 102206,China;MOE Key Laboratory of Resources and Environmental System Optimization,College of Environmental Science and Engineering,North China Electric Power University,Beijing 102206,China)
机构地区:[1]华北电力大学数理学院,北京102206 [2]华北电力大学控制与计算机工程学院,北京102206 [3]华北电力大学资源环境系统优化教育部重点实验室,北京102206
出 处:《无机材料学报》2021年第8期871-876,共6页Journal of Inorganic Materials
基 金:科技部重大研发计划(2018YFC1900105,2017YFA0207002);中央高校基本科研业务费专项资金(2019MS040)。
摘 要:光催化去除水中污染物的研究通常得到的是小样本的离散数据,利用拟一级动力学模型对实验结果进行模拟和分析,有时拟合效果较差,且无法用于数据预测。本研究在离散灰色预测模型(DGM(1,1))的基础上,考虑数据的非线性特征并结合等维信息替代思想建立了非线性动态离散灰色模型(EDGM(1,1,α)),利用该模型对三元复合材料Bi/BiOCl/Au光催化去除四环素实验所得数据进行了预测,其平均相对误差和拟合度数据显示:相比于DGM(1,1)等3种模型,EDGM(1,1,α)模型对光催化实验数据具有良好的预测水平,与实验结果吻合。该预测方法可以用于指导下一步实验,有望减少实验次数,降低成本和能耗。Discrete and small samples data are usually obtained from the studies on photocatalytic removal of pollutants in water.The first-order kinetic model used to simulate and analyze the experimental data sometimes has poor fitting effect and cannot be used for data prediction.In this study,based on the discrete grey model(DGM(1,1)),the nonlinear dynamic discrete gray model(EDGM(1,1,α))are established by considering the nonlinear characteristics of the data and equal dimensional information substitution method.The model is used to predict the experimental data of photocatalytic degradation of tetracycline by Bi/BiOCl/Au.As compared with DGM(1,1)and other three models,the EDGM(1,1,α)model has a better prediction level for the experimental data of photocatalysis.The results are in good agreement with the experimental results.This model can be used to guide the next step of experiments,which is expected to reduce the number of experiments and realize the rapid development of experimental research with low cost and energy consumption.
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