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A METHOD OF WAVELET-BASED AUTOREGRESSIVE FUZZY MODELING FOR FORECASTING ALGAL BLOOMS

机译:一种基于小波的藻类自动回归模糊预测模型

摘要

The present invention relates to a fuzzy modeling method for predicting algal blooms, comprising: a first step for receiving input of water quality and hydrological data; a second step for calculating a coefficient of correlation between input/output signals; a third step for applying a wavelet transform analysis technique to filter noise signals from the input/output signals; a fourth step for applying a subtractive clustering algorithm to determine a premise parameter using the input/output signals filtered; a fifth step for optimizing a consequent parameter using a weighted least squares algorithm; a sixth step for returning to the fourth step if an error has a value greater than an allowed error value, and proceeding to the next step if less than the allowed error value; and a seventh step for testing validity of a model.
机译:本发明涉及一种用于预测藻华的模糊建模方法,包括:接收水质和水文数据输入的第一步;第二步,计算输入/输出信号之间的相关系数;第三步,应用小波变换分析技术从输入/输出信号中滤除噪声信号;第四步骤,应用减法聚类算法来使用滤波后的输入/输出信号来确定前提参数;第五步骤,使用加权最小二乘算法优化结果参数;第六步骤,如果错误的值大于允许的错误值,则返回到第四步骤,如果小于允许的错误值,则进行到下一步;以及测试模型有效性的第七步。

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