基于BP神经网络的GPS导航算法     

高为广赵文军  李洪力孙岩峰 《测绘科学与工程》2006,26(2):47-50

GPS导航解算中常用最小二乘算法。随着高动态用户需求精度的不断提高，且由于线性化忽略高次项，初始值精度低以及差分后剩余或放大误差的存在。导航解精度很难满足高动态用户的需求。为此，本文基于BP神经网络的非线性逼近性能。给出了基于BP神经网络的GPS导航算法。实测数据计算结果表明该算法能够真实地反映载体运动轨迹，其导航解的精度和可靠性有明显的提高。  相似文献   

Integration of transfer function model and back propagation neural network for forecasting storm sewer flow in Taipei metropolis     

Chih-Chiang Lu  Chu-Hui Chen  Tian-Chyi J. Yeh  Cheng-Mau Wu  I-Fang Yau 《Stochastic Environmental Research and Risk Assessment (SERRA)》2006,20(1-2):6-22

Typhoons and storms have often brought heavy rainfalls and induced floods that have frequently caused severe damage and loss of life in Taiwan. Our ability to predict sewer discharge and forecast floods in advance during storm seasons plays an important role in flood warning and flood hazard mitigation. In this paper, we develop an integrated model (TFMBPN) for forecasting sewer discharge that combines two traditional models: a transfer function model and a back propagation neural network. We evaluated the integrated model and the two traditional models by applying them to a sewer system of Taipei metropolis during three past typhoon events (NARI, SINLAKU, and NAKR). The performances of the models were evaluated by using predictions of a total of 6 h of sewer flow stages, and six different evaluation indices of the predictions. Finally, an overall performance index was determined to assess the overall performance of each model. Based on these evaluation indices, our analysis shows that TFMBNP yields accurate results that surpass the two traditional models. Thus, TFMBNP appears to be a promising tool for flood forecasting for the Taipei metropolis sewer system. For publication in Stochastic Environmental Research and Risk Analysis.  相似文献   

ANN技术在岩溶地下水可开采量评价中的应用——以山西晋祠泉域为例     

殷丹  苏小四  李砚阁  冯玉明 《吉林大学学报(地球科学版)》2006,(Z1)

以晋祠泉域为例,分析该泉域水文地质特征。应用神经网络技术(ANN)建立泉域内县代表性的难老泉岩溶地下水位与各种补排项之间定量数学模型,对该泉域地下水可开采量进行了评价。研究结果表明,所建立的岩溶地下水位多因素神经网络模型具有较好的拟合精度,仿真程度较高,所得到的地下水可采资源量评价结果与该地区地下水开发利用实际情况较为一致。同时,还计算了不同降雨条件下地下水的可开采量,使其对地下水的开采规划更具有指导意义。  相似文献   

DOWNSCALING FORECAST OF MONTHLY PRECIPITATION OVER GUANGXI BASED ON BP NEURAL NETWORK MODEL     

何慧  金龙  覃志年  袁丽军 《热带气象学报(英文版)》2007,13(1):97-100

Variables fields such as enstrophy, meridional-wind and zonal-wind variables are derived from monthly 500 hPa geopotential height anomalous fields. In this work, we select original predictors from monthly 500-hPa geopotential height anomalous fields and their variables in June of 1958 - 2001, and determine comprehensive predictors by conducting empirical orthogonal function (EOF) respectively with the original predictors. A downscaling forecast model based on the back propagation (BP) neural network is built by use of the comprehensive predictors to predict the monthly precipitation in June over Guangxi with the monthly dynamic extended range forecast products. For comparison, we also build another BP neural network model with the same predictands by using the former comprehensive predictors selected from 500-hPa geopotential height anomalous fields in May to December of 1957 - 2000 and January to April of 1958 - 2001. The two models are tested and results show that the precision of superposition of the downscaling model is better than that of the one based on former comprehensive predictors, but the prediction accuracy of the downscaling model depends on the output of monthly dynamic extended range forecast.  相似文献   

GPS测量在巴郎沟水电站施工控制网中的应用     

胡万兵  何廷贵 《测绘信息与工程》2007,32(3):36-37

介绍了巴郎沟水电站GPS施工控制网的布设、基线处理及平差方法,分析了GPS施工控制网精度及基线粗差,实现了在隐蔽地区较高精度GPS施工测量的应用.  相似文献   

Neo-liberal ruptures: Local political entities and neighbourhood networks in El Alto, Bolivia     

Juan Manuel Arbona 《Geoforum》2007,38(1):127-137

In October 2003, hundreds of thousands of Bolivians took to the streets demanding the resignation of President Gonzalo Sánchez de Lozada. After 20 years of neo-liberal policies - and the failures to improve the living conditions of the majority - the proposal to export natural gas via Chile was taken by the population as yet another step to sustain an unjust political order. Facing a direct challenge by the population the Sánchez de Lozada administration responded with indiscriminate military force. The result was 63 dead and over 300 wounded, which deepened and extended the social rage and eventually forced the resignation of the President. The neo-liberal project - promoted and defended by Sánchez de Lozada - collapsed. The city of El Alto was the epicentre of the challenges to the legitimacy of this political order. This article focuses on the role of local political entities and neighbourhood networks from El Alto in articulating political spaces that challenged the legitimacy of the institutional infrastructure and led to the October 2003 ruptures in the neo-liberal project. Furthermore, I make the case that the particular histories and memories (of “relocalized” miners and indigenous/peasants) that converged in and defined this city were pivotal in the organization of a “political subsoil” that surged to the surface during the October 2003 events.  相似文献   

数据挖掘技术在水文预报中的应用及水文预报发展趋势研究   总被引：2，自引：1，他引：2  

张弛  王本德  李伟 《水文》2007,27(2):74-77,85

数据挖掘作为知识发现过程中的重要步骤,是从大型数据库中提取未知的、有价值的和可操作性的关系、模式和趋势用于决策支持的过程。我国目前在防洪领域存在着大量水文数据,如何充分有效地利用各种智能算法对这些数据进行分析与挖掘,以形成相应的水文预报模型进行准确的水文预报是防洪决策支持系统完善和发展的重要方面。本文首先全面地介绍数据挖掘的功能分类及以数据挖掘为基础的水文预报体系,然后对数据挖掘技术在水文预报中的应用进行了探讨和研究。  相似文献   

地震多参数神经网络储层油气预测中的参数优化     

张惠珍  王山山  马良 《物探化探计算技术》2007,29(5):420-424

在利用多参数进行储层油气预测时,并不是使用的特征越多越好,最佳特征的维数取决于实际问题的预测效果。这里运用聚类分析法优选地震特征参数,将距离较远或相似系数低的特征参数聚为一类,用来对未知样本进行地震储层预测。利用优选后的参数进行神经网络储层油气预测,在实际应用时取得了较好的效果。  相似文献   

基于新型仿生智能方法的边坡变形位移预测     

薛源  胡丹  郭科  张军 《物探化探计算技术》2007,29(5):446-449

边坡地变形,具有高度复杂的非线性演化特征。将BP神经网络和免疫克隆算法改进并集成结合,提出一种新型的仿生智能方法,即免疫克隆神经网络。并利用其强大的非线性拟合能力,对边坡进行变形位移的预测。结果表明,此方法拥有较高的预测精度,为边坡变形位移的预测提供了行之有效的途径,从而为边坡稳定性判别和滑坡预报提供了可靠的分析依据。  相似文献   

A Comparison between a Modified Counter Propagation Network and an Extended Self-Organizing Map in Remotely Sensed Data Classification     

Yongliang Chen  Micha I. Pazner  Wei Wu 《Mathematical Geology》2007,39(6):559-574

A modified counter propagation network model and an extended self-organizing map model have the same three-layer network architecture while employing slightly different learning rules. Their network architecture comprises an input layer, a Kohonen layer and an output layer. The neurons between two neighboring layers are fully connected and the neighboring neurons within the Kohonen layer also have neighborhood connections. The modified counter propagation network model employs the Kohonen algorithm to train the Kohonen layer while using the Widrow–Hoff rule to train the output layer. However, the extended self-organizing map model applies a modified Kohonen’s learning rule to train both the Kohonen layer and the output layer. This paper compares the performances of these two models in supervised classification of remotely sensed data. The training results show that compared to the extended self-organizing map model, the modified counter propagation model has faster learning speed but larger output errors. The classification results indicate that the extended self-organizing map model has a faster classification speed and a much higher classification precision than the modified counter propagation model.  相似文献