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Adaptive neuro-fuzzy inference technique for estimation of light penetration in reservoirs

机译:自适应神经模糊推理技术估算储层光穿透

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摘要

An adaptive neuro-fuzzy inference technique has been adopted to estimate light levels in a reservoir. The data were collected randomly from Doğanci Dam Reservoir over a number of years. The input data set is a matrix with vectors of time, depth, sampling location, and incident solar radiation. The output data set is a vector representing light measured at various depths. Randomization and logarithmic transformations have been applied as preprocessing. One-half of the data have been utilized for training; testing and validation steps utilized one-fourth each. An adaptive neuro-fuzzy inference system (ANFIS) has been built as a prediction model for light penetration. Very high correlation values between predictions and real values on light measurements with relatively low root mean square error values have been obtained for training, test, and validation data sets. Elimination of the overtraining problem was ensured by satisfying close root mean square error values for all sets.
机译:自适应神经模糊推理技术已被用来估计储层中的光照水平。多年来,这些数据是从杜安奇大坝水库中随机收集的。输入数据集是一个矩阵,其中包含时间,深度,采样位置和太阳辐射入射向量。输出数据集是一个矢量,表示在各种深度下测得的光。随机化和对数转换已被用作预处理。一半的数据已用于培训;测试和验证步骤各使用四分之一。自适应神经模糊推理系统(ANFIS)已被构建为光穿透的预测模型。对于训练,测试和验证数据集,已经获得了具有相对较低的均方根误差值的光测量值的预测值与实际值之间的非常高的相关值。通过满足所有集合的近似均方根误差值,可以确保消除过度训练问题。

著录项

  • 来源
    《Limnology》 |2007年第2期|103-112|共10页
  • 作者单位

    Faculty of Engineering Department of Civil Engineering Atilim University Kizilcaşar Köyü İncek Ankara 06836 Turkey;

    Faculty of Engineering and Architecture Department of Environmental Engineering Uludağ University Bursa Turkey;

    State Hydraulic Works of Turkey 1st Division Bursa Turkey;

    State Hydraulic Works of Turkey 1st Division Bursa Turkey;

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

    Reservoirs; Modeling; Light penetration; Neuro-fuzzy inference; ANFIS;

    机译:储层;建模;光穿透;神经模糊推理;ANFIS;

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