Identification of physical processes inherent in artificial neural network rainfall runoff models     

Ashu Jain  K. P. Sudheer  Sanaga Srinivasulu 《水文研究》2004,18(3):571-581

The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

Generalized strain probing of constitutive models     

Youssef M. A. Hashash  Qingwei Fu  Jeremy Butkovich 《国际地质力学数值与分析法杂志》2004,28(15):1503-1519

Advanced material constitutive models are used to describe complex soil behaviour. These models are often used in the solution of boundary value problems under general loading conditions. Users and developers of constitutive models need to methodically investigate the represented soil response under a wide range of loading conditions. This paper presents a systematic procedure for probing constitutive models. A general incremental strain probe, 6D hyperspherical strain probe (HSP), is introduced to examine rate‐independent model response under all possible strain loading conditions. Two special cases of HSP, the true triaxial strain probe (TTSP) and the plane‐strain strain probe (PSSP), are used to generate 3‐D objects that represent model stress response to probing. The TTSP, PSSP and general HSP procedures are demonstrated using elasto‐plastic models. The objects resulting from the probing procedure readily highlight important model characteristics including anisotropy, yielding, hardening, softening and failure. The PSSP procedure is applied to a Neural Network (NN) based constitutive model. It shows that this probing is especially useful in understanding NN constitutive models, which do not contain explicit functions for yield surface, hardening, or anisotropy. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

Automatic Determination of Stellar Atmospheric Parameters Using Neural Networks and Instance-Based Machine Learning     

Olac Fuentes 《Experimental Astronomy》2001,12(1):21-31

In this article we show how machine learning methods can beeffectively applied to the problem of automatically predictingstellar atmospheric parameters from spectral information, a veryimportant problem in stellar astronomy. We apply feedforwardneural networks, Kohonen's self-organizing maps andlocally-weighted regression to predict the stellar atmosphericparameters effective temperature, surface gravity and metallicityfrom spectral indices. Our experimental results show that thethree methods are capable of predicting the parameters with verygood accuracy. Locally weighted regression gives slightly betterresults than the other methods using the original dataset asinput, while self-organizing maps outperform the other methods when significant amounts of noise are added. We also implemented a heterogeneous ensemble of predictors, combining the results given by the three algorithms. This ensemble yields better results than any of the three algorithms alone, using both the original and the noisy data.  相似文献   

关于网络用户经济效益评测模型的研究     

岳正华  李黎 《成都信息工程学院学报》2001,16(2):141-144

着重讨论了网络用户经济效益的内涵以及用户的投入量和产出量，并提出了评价网络用户经济效益的指标体系，包括成本降低率，成本利润增长率、产品开发时间约率、市场占有增长率等系列指标。  相似文献   

卫星激光测距的新进展   总被引：6，自引：0，他引：6  

张忠萍  杨福民 《天文学进展》2001,19(2):283-288

扼要综述了近几年国际上卫星激光测距的进展，介绍了国内激光测距网的现状，展望了未来卫星激光测距的发展。  相似文献   

VPN技术在浙江省气象网络中的应用   总被引：2，自引：0，他引：2  

吴孟春  马奇蔚  周必高  周捷  周翔 《成都信息工程学院学报》2006,21(4):551-554

随着浙江省气象业务的不断发展，网络数据交换日益增多，同时更多基于网络的气象业务的增加，如网络视频会商、自动站数据传输等，使目前浙江省气象系统专线网络运行已达到极限，所以需要建立VPN网以对现有的网络作链路上的备份，而VPN的建立同时还可以实现移动办公，领导能在远程调用内网的资料进行远程决策服务和汇报工作。主要介绍VPN技术并叙述VPN技术在浙江省气象系统网络中的具体应用。  相似文献   

黄土斜坡稳定性的模糊信息分析法     

王家鼎  冯学才  孟兴民 《山地学报》1991,(1)

本文基于黄土斜坡稳定性的实际资料,利用信息分配、模糊一二级近似推论及信息集中等原因建立了一套黄土斜坡稳定性的评价方法。用这套方法对一些黄土斜坡(非母体)稳定性进行了验证,其结果与实际情况一致。本方法已应用于兰州市滑坡防灾规划和皋兰山三台阁北侧几个滑坡及斜坡稳定性的研究中,效果良好。  相似文献   

水下滑翔器主体外形优化设计   总被引：2，自引：0，他引：2  

王兵振  朱光文  杜敏  任炜  李永奇 《海洋技术学报》2008,27(3)

对水下滑翔器主体外形的优化设计问题进行研究.首先,在考虑内部机械结构限制的条件下,建立了主体外形优化数学模型,并采用CFX计算了若干主体形状的绕流阻力.在此基础上建立了映射主体外形的尺寸参数与绕流阻力的BP神经网络.然后将建立的神经网络作为优化设计问题的目标函数,采用坐标轮换法对滑翔器主体外形进行了优化设计,确定了尺寸参数的最优解.  相似文献   

关于网络企业经济效益的评价理论研究     

岳正华  李黎 《成都信息工程学院学报》2001,16(3):192-198

网络经济是相对于大工业经济而言的，其网络企业经济效益的评价，可以从网络企业成本及收益两个方面讨论，然后以投入产出比等五个方面来建立其评价指标体系。  相似文献   

区域GPS网实时计算可降水量的若干问题   总被引：1，自引：0，他引：1  

SONG Shuli ZHU Wenyao 《中国科学院上海天文台年刊》2003,(1)

目前地基GPS气象学测得的可降水量 (PWV )精度好于 2mm ,但在利用区域GPS网实时计算每个测站上空的PWV时 ,要涉及到很多常规GPS资料处理时所忽略的问题 ,如需考虑数据处理软件和计算方式的选择、站坐标的确定和约束、轨道的使用方法、网外辅助站最佳数量的确定、海潮对实时计算PWV的影响以及实时应用于气象服务时的端部效应等问题。利用上海GPS综合应用网获取的 2 0 0 2年 6、7月份长江三角洲地区入梅前后的数据 ,分析了利用区域性的GPS网实时计算高精度的PWV时要解决的各种问题 ,探讨了其数据处理方案  相似文献