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Functional Link Neural Network Prediction on Composite Regeneration Time of Diesel Particulate Filter for Vehicle Based on Fuzzy Adaptive Variable Weight Algorithm

机译:基于模糊自适应变权算法的车用柴油机颗粒过滤器复合再生时间的功能链接神经网络预测。

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摘要

In order to enhance the precision of prediction on composite regeneration time of diesel particulate filter for vehicle, different predictive values of each prediction model are selected as the primeval input values of functional link neural network, and the functional link neural network prediction model of composite regeneration time based on fuzzy adaptive variable weight algorithm is established after the necessary and sufficient conditions for fitting of functional link neural network are analyzed. The application result of the model shows that the absolute value |e_(max)| of maximum relative error of functional link neural network prediction model on composite regeneration time of diesel particulate filter for vehicle based on fuzzy adaptive variable weight algorithm is less than 0.86%, indicating the high accuracy of the prediction model. Moreover, the result draws that the factors influencing composite regeneration time prediction of diesel particulate filter for vehicle, influence degree of which is from big to small, are exhaust oxygen concentration, exhaust mass flow, microwave power, exhaust temperature and the amount of cerium-based additive.
机译:为了提高车辆柴油颗粒滤清器复合再生时间的预测精度,选择每种预测模型的不同预测值作为功能链接神经网络的原始输入值,并采用复合链接的功能链接神经网络预测模型在分析了功能链接神经网络拟合的充要条件后,建立了基于模糊自适应变权算法的时间估计方法。模型的应用结果表明,绝对值| e_(max)|基于模糊自适应变权算法的功能链接神经网络预测模型的最大相对误差对车辆柴油颗粒滤清器复合再生时间的小于0.86%,表明该预测模型具有较高的准确性。此外,结果得出影响车辆柴油颗粒滤清器复合再生时间预测的因素,其影响程度从大到小,分别是排气氧浓度,排气质量流量,微波功率,排气温度和铈含量。添加剂。

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  • 来源
    《Journal of information and computational science》 |2014年第6期|1741-1751|共11页
  • 作者单位

    State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Changsha 410082, China,College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China;

    College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China;

    State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Changsha 410082, China,College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China;

    College of Mechanical and Electrical Engineering, Central South University of Forestry and Technology, Changsha 410004, China;

    State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Changsha 410082, China,College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China;

    State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Changsha 410082, China;

    College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Functional Link Neural Network; Diesel Particulate Filter; Composite Regeneration Time;

    机译:功能链接神经网络;柴油颗粒过滤器;复合再生时间;

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