Ecosystem health assessment of Honghu Lake Wetland of China using artificial neural network approach   总被引：3，自引：0，他引：3  

Minghao Mo  Xuelei Wang  Houjian Wu  Shuming Cai  Xiaoyang Zhang  Huiliang Wang 《中国地理科学(英文版)》2009,19(4):349-356

Honghu Lake, located in the southeast of Hubei Province, China, has suffered a severe disturbance during the past few decades. To restore the ecosystem, the Honghu Lake Wetland Protection and Restoration Demonstration Project (HLWPRDP) has been implemented since 2004. A back propagation (BP) artificial neural network (ANN) approach was applied to evaluatinig the ecosystem health of the Honghu Lake wetland. And the effectiveness of the HLWPRDP was also assessed by comparing the ecosystem health before and after the project. Particularly, 12 ecosystem health indices were used as evaluation parameters to establish a set of three-layer BP ANNs. The output is one layer of ecosystem health index. After training and testing the BP ANNs, an optimal model of BP ANNs was selected to assess the ecosystem health of the Honghu Lake wetland. The result indicates that four stages can be identified based on the change of the ecosystem health from 1990 to 2008 and the ecosystem health index ranges from morbidity before the implementation of HLWPRDP (in 2002) to middle health after the implementation of the HLWPRDP (in 2005). It demonstrates that the HLWPRDP is effective and the BP ANN could be used as a tool for the assessment of ecosystem health.  相似文献   

一种基于BP神经网络的空间异常探测方法     

李光强  刘启亮  邓敏 《测绘科学技术学报》2009,26(6)

空间异常探测旨在发现偏离普遍模式的小部分异常目标.对揭示地理现象潜在的发展变化规律有着重要意义.在现有的空间异常探测方法中,空间邻近域的确定直接影响探测结果的可靠性.为此,在顾及空间数据分布特征的前提下,利用人工神经网络机器学习的优势,发展了面向空间异常探测的BP神经网络结构和学习规则,提出了基于BP神经网络的空间异常探测方法,定义了基于BP神经网络的空间异常度概念,进而探测空间异常.最后,通过3组实际算例验证所提方法的可行性,并分析得出实验结论.  相似文献   

Retrieval of water vapor profiles with radio occultation measurements using an artificial neural network   总被引：3，自引：1，他引：2  

WANG Xin  Lü Daren 《大气科学进展》2005,22(5):759-764

A new method applying an artificial neural network （ANN） to retrieve water vapor profiles in the troposphere is presented. In this paper, a fully-connected, three-layer network based on the backpropagation algorithm is constructed. Month, latitude, altitude and bending angle are chosen as the input vectors and water vapor pressure as the output vector. There are 130 groups of occultation measurements from June to November 2002 in the dataset. Seventy pairs of bending angles and water vapor pressure profiles are used to train the ANN, and the sixty remaining pairs of profiles are applied to the validation of the retrieval. By comparing the retrieved profiles with the corresponding ones from the Information System and Data Center of the Challenging Mini-Satellite Payload for Geoscientific Research and Application （CHAMP-ISDC）, it can be concluded that the ANN is relatively convenient and accurate. Its results can be provided as the first guess for the iterative methods or the non-linear optimal estimation inverse method.  相似文献   

基于 BP 神经网络法求解土的前期固结压力     

高学峰 《地下水》2014,(3):163-164

运用人工神经网络原理,提出基BP神经网络求解前期固结压力的模型。在MATLAB7．12．0平台上编程实现BP模型,并通过实例求解,预测结果比较好,说明BP人工神经网络求解前期固结压力是可行的。  相似文献   

基于 BP 人工神经网络算法的临沂市土地利用集约状况探析     

王荣华  刘荔  孟婷婷 《山东地质》2014,(11):84-86

通过对2009—2012年度临沂市9县3区统计年鉴和变更调查中11个相关指标数据的搜集,借助 MATLAB7．0软件平台,利用 BP 人工神经网络算法,算出2009—2012年度各县区土地利用集约度,并利用 BP 人工神经网络的预测功能,预测了2013年和2014年度土地利用集约度值,结果表明临沂市平均土地利用集约度水平正逐步从粗放利用发展到中度集约,兰山区土地利用集约度水平一直为高度集约,集约度居全市之首,罗庄区一直为中度集约,稳中有进。预计到2014年底,大部分县区在中度集约或以上,仅有费县、蒙阴2县为粗放利用。。  相似文献   

GPS掩星技术和电离层反演   总被引：13，自引：6，他引：7  

周义炎  吴云  乔学军  张训械 《大地测量与地球动力学》2005,25(2):29-35

系统地介绍了GPS无线电掩星技术的发展现状、系统组成和一些关键技术；论述了利用GPS掩星数据进行电离层反演的理论、模型及相应的计算流程．并结合GPS／MET和CHAMP卫星的实测资料，计算了电子密度剖面，与用其他方法所得结果的对比表明．GPS掩星电离层观测具有精度高、覆盖范围大等特点；最后讨论了GPS掩星技术应用于地震前兆监测的机理和前景。  相似文献   

SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK     

WANGXie-kang HUANGEr CUIPeng 《中国地理科学(英文版)》2003,13(3):262-266

Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.  相似文献   

水污染物浓度的神经网络预测模式及效果检验     

于扬  薛丽梅  聂伊辰 《成都信息工程学院学报》2004,19(1):100-103

污染物浓度预测是环境保护的重要内容,将神经网络用于水中有机污染物浓度的预测并对效果进行检验.结果表明,预测值与观测值符合较好.  相似文献   

河北省环渤海地区生态经济协调发展的人工神经网络分析   总被引：11，自引：2，他引：9  

李双成  高伟明  刘濂 《地理研究》1998,17(4):352-359

区域社会经济系统的可持续发展依赖于系统成分的协调程度及与生态系统的增益耦合。传统研究多以系统动力学或多目标规划模型来调控系统。文中以人工神经网络模型来模拟和映射社会经济系统的结构和功能。通过构建、训练、测试、运行河北省环渤海地区生态经济网络模型,提出了以减缓发展速度、降低能量投入水平等措施来达到生态系统和社会经济系统协调发展的目标。  相似文献   

深基坑工程变形预报神经网络法的初步研究   总被引：33，自引：0，他引：33  

孙海涛  吴限 《岩土力学》1998,19(4):63-68

提出了深基坑变形预报的人工神经网络法,详细介绍了该方法的建模和应用实例。预报结果与实测值较为吻合,从而表现在深基坑工程中利用该方法进行变形预报是可行的。  相似文献