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1.
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
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INTRODUCTIONTriploidanimalsareusefulbecausetheyaresterile ,characterizedbypositivegrowthinthere productiveseason ,usefulfortesting ,forintroductionofnon nativespecies ,andforprotectionofde velopedstrains.Theinductionoftriploidyhadbeenreportedinmanyaquaculturespecies .Triploidshavebeensuccessfullyinducedinshrimpusingtemperatureshockorchemicalshock (CB ,6 DMAP)in 4species :Sicyoniaingentis (Xiangetal.,1 991 ) ,Fenneropenaeuschinensis (Xiangetal.,1 992 ;Daietal.,1 993;Baoetal.,1 993;Li… 相似文献
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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
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形变大地测量学的进展、问题与地震预报 总被引:12,自引:7,他引:5
简要概括了形变大地测量学的革命性进展,研讨了它的科学特色、功能和定义以及对地球科学和防灾减灾的推动。形变大地测量学有助于从根本上击破多年来制约地震预报的“瓶颈”,但也存在不少急待解决的问题。着重研讨了在21世纪前10年,形变大地测量学如何依托多年的学科积累并充分受益于人造卫星和数字化等新技术,开展创新性研究和试验以推进地震预报。为此,对当前的研究工作提出了12条科学技术途径。最后对学科名称提出了建议。 相似文献
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Singh et al (2005) examined the potential of the ANN and neuro-fuzzy systems application for the prediction of dynamic constant of rockmass.
However, the model proposed by them has some drawbacks according to fuzzy logic principles. This discussion will focus on
the main fuzzy logic principles which authors and potential readers should take into consideration. 相似文献
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基于现场实验数据集及人工神经网络技术,论文提出了一种从海中粒子吸收光谱提取浮游植物吸收光谱的方法。这个数据集包含了海中粒子吸收光谱和对应的浮游植物吸收光谱,并被分为三个子集:训练集、印证集和试验集。本研究所利用的人工神经网络系统为多层感知器,训练后的人工神经网络的性能由印证集和试验集来评价。实验结果表明,文中所提出的方法可成功地提取浮游植物的吸收光谱,其提取精度与传统的实验方法相当。 相似文献
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