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Research on One Intelligent Prediction Method for Water Bloom

机译:一种水华智能预测方法的研究

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An intelligent method on short-term prediction on water bloom of BP neural network based on rough set and wavelet analysis is proposed in this paper. This method analyzes factors of effecting the outbreak of water bloom, and these many factors which were processed by reduction method based on rough set were used as input information of the prediction model; after analyzing the main input information by wavelet multi-resolution, it can eliminate the interference factors in the input information, and use BP network to establish the non-linear relationship between input factors and result of water bloom prediction. After experimental simulation, it can validate that this kind of short-term forecast model can predict the short-term change regularity of chlorophyll more precisely, and provides an efficient new method for short-term prediction of water bloom
机译:提出了一种基于粗糙集和小波分析的BP神经网络水华短期预测方法。该方法分析了影响水华爆发的因素,并将这些基于粗糙集的折减法处理后的许多因素作为预测模型的输入信息。通过小波多分辨率对主要输入信息进行分析后,可以消除输入信息中的干扰因素,并利用BP网络建立输入因素与水华预报结果之间的非线性关系。经过实验模拟,可以验证这种短期预报模型能够更准确地预测叶绿素的短期变化规律,为短期预测水华提供了一种有效的新方法。

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