BP神经网络的非线性系统建模matlab源码

当今,环境污染问题已经成为人类面对的一个日益严重的问题。只有准确掌握环境污染的实际情况,才能对污染问题采取行之有效的措施。这就要求我们对当前的环境污染状况做出准确,客观的评价。为了客观,高效地完成全国各地农业环境的质量评估工作,新一代的农业环境质量评价软件――农业部环境分析评价系统应运而生。农业部环境分析评价系统采用动态BP神经网络模型和模糊综合评价模型对各全国各地区的土壤,空气,灌溉水三个环境要素的污染状况以及各地区的总体环境质量进行评估。环境分析评价系统是计算机软件技术与环境质量评估工作相结合的典型实例,也是将BP神经网络模型（Bcrmefd Sengcetens,BP）,模糊综合评价方法,和计算机技术应用于环境质量评估的典型实例。而这篇论文也围绕农业部环 境分析评价系统为核心集中展开。这篇论文共分为六个部分。 文章第一部分对环境分析评价系统的功能和由来进行了简要的介绍; 文章第二部分介绍了环境分析评价系统的理论模型的选择过程; 文章第三部分对动态BP神经网络模型,树文网wWw.KuaiLEunwen.com,该模型在环境质量评价中的应用,以及该模型在环境分析评价系统中的具体实现情况进行了介绍;文章第四部分则介绍了模糊综合评价模型,该模型在环境质量评价中的应用,以及该模型在环境分析评价系统中的具体实现情况; 文章第五部分对农业部环境分析评价系统对实际监测数据的评估结果进行了分析,并提出了作者自己的观点。 文章的最后一部分对现有的工作成果进行了总结,并提出了对未来工作的展望。 部分英文描述： Building wind power prediction system and improve its prediction accuracy is one of the key technology of large-scale wind power development. Based on the numerical weather prediction, a back propagation (BP) neural network is wind power prediction model, and adopts a wind farm real data analysis of the factors influencing the accuracy of the model. In view of the original wind speed and power, the sequence is not obvious, the BP neural network can't map the features of defect, put forward a wavelet - based on the BP neural network prediction model. The model using wavelet will wind speed and power series are decomposed on different scales, and the use of multiple BP neural network to predict each frequency component and finally reconstruct complete forecasting results are obtained. Studies have shown that the model can effectively improve the prediction precision. 境分析评价系统为核心集中展开。这篇论文共分为六个部分。 文章第一部分对环境分析评价系统的功能和由来进行了简要的介绍; 文章第二部分介绍了环境分析评价系统的理论模型的选择过程; 文章第三部分对动态BP神经网络模型,树文网wWw.KuaiLEunwen.com,该模型在环境质量评价中的应用,以及该模型在环境分析评价系统中的具体实现情况进行了介绍;文章第四部分则介绍了模糊综合评价模型,该模型在环境质量评价中的应用,以及该模型在环境分析评价系统中的具体实现情况; 文章第五部分对农业部环境分析评价系统对实际监测数据的评估结果进行了分析,并提出了作者自己的观点。 文章的最后一部分对现有的工作成果进行了总结,并提出了对未来工作的展望。 部分英文描述： Building wind power prediction system and improve its prediction accuracy is one of the key technology of large-scale wind power development. Based on the numerical weather prediction, a back propagation (BP) neural network is wind power prediction model, and adopts a wind farm real data analysis of the factors influencing the accuracy of the model. In view of the original wind speed and power, the sequence is not obvious, the BP neural network can't map the features of defect, put forward a wavelet - based on the BP neural network prediction model. The model using wavelet will wind speed and power series are decomposed on different scales, and the use of multiple BP neural network to predict each frequency component and finally reconstruct complete forecasting results are obtained. Studies have shown that the model can effectively improve the prediction precision.