ARTIFICIAL NEURAL NETWORK CORRECTION OF ROUGH ERRORS OF OBSERVATIONS   总被引：1，自引：0，他引：1       下载免费PDF全文

蒋国荣  张韧  沙文钰  阎俊岳  姚华栋 《Acta Meteorologica Sinica》2002,(1)

In the context of tower measured radiation datasets.following the correction principle meetinga diagnostic equation in data quality control and in terms of a technique for model construction ondata and ANN(artificial neural network)retrieval for BP correction of radiation measurementswith rough errors available,a BP model is presented.Evidence suggests that the developed modelworks well and is superior to a convenient multivariate linear regression model,indicating its wideapplications.  相似文献   

An integrated hydrological model for rain‐induced landslide prediction     

P. L. Wilkinson  M. G. Anderson  D. M. Lloyd 《地球表面变化过程与地形》2002,27(12):1285-1297

This paper describes an extension to the Combined Hydrology And Stability Model (CHASM) to fully include the effects of vegetation and slope plan topography on slope stability. The resultant physically based numerical model is designed to be applied to site‐specific slopes in which a detailed assessment of unsaturated and saturated hydrology is required in relation to vegetation, topography and slope stability. Applications are made to the Hawke's Bay region in New Zealand where shallow‐seated instability is strongly associated with spatial and temporal trends in vegetation cover types, and the Mid‐Levels region in Hong Kong, an area subject to a variety of landslide mechanisms, some of which may be subject to strong topographic control. An improved understanding of process mechanism, afforded by the model, is critical for reliable and appropriate design of slope stabilization and remedial measures. Copyright © 2002 John Wiley & Sons, Ltd.  相似文献   

Structural damage detection using the optimal weights of the approximating artificial neural networks     

Shih‐Lin Hung  C. Y. Kao 《地震工程与结构动力学》2002,31(2):217-234

This work presents a novel neural network‐based approach to detect structural damage. The proposed approach comprises two steps. The first step, system identification, involves using neural system identification networks (NSINs) to identify the undamaged and damaged states of a structural system. The partial derivatives of the outputs with respect to the inputs of the NSIN, which identifies the system in a certain undamaged or damaged state, have a negligible variation with different system errors. This loosely defined unique property enables these partial derivatives to quantitatively indicate system damage from the model parameters. The second step, structural damage detection, involves using the neural damage detection network (NDDN) to detect the location and extent of the structural damage. The input to the NDDN is taken as the aforementioned partial derivatives of NSIN, and the output of the NDDN identifies the damage level for each member in the structure. Moreover, SDOF and MDOF examples are presented to demonstrate the feasibility of using the proposed method for damage detection of linear structures. Copyright © 2001 John Wiley & Sons, Ltd.  相似文献   

Modelling evaporation using an artificial neural network algorithm   总被引：1，自引：0，他引：1  

K. P. Sudheer  A. K. Gosain  D. Mohana Rangan  S. M. Saheb 《水文研究》2002,16(16):3189-3202

This paper investigates the prediction of Class A pan evaporation using the artificial neural network (ANN) technique. The ANN back propagation algorithm has been evaluated for its applicability for predicting evaporation from minimum climatic data. Four combinations of input data were considered and the resulting values of evaporation were analysed and compared with those of existing models. The results from this study suggest that the neural computing technique could be employed successfully in modelling the evaporation process from the available climatic data set. However, an analysis of the residuals from the ANN models developed revealed that the models showed significant error in predictions during the validation, implying loss of generalization properties of ANN models unless trained carefully. The study indicated that evaporation values could be reasonably estimated using temperature data only through the ANN technique. This would be of much use in instances where data availability is limited. Copyright © 2002 John Wiley & Sons, Ltd.  相似文献   

Momentum transport of wave zero during March: A possible predictor for the Indian summer monsoon     

S. M. Bawiskar  V. R. Mujumdar  S. S. Singh 《Journal of Earth System Science》2002,111(2):153-157

Analysis of monthly momentum transport of zonal waves at 850 hPa for the period 1979 to 1993, between ‡S and ‡N for January to April, using zonal (u) and meridional (v) components of wind taken from the ECMWF reanalysis field, shows a positive correlation (.1% level of significance) between the Indian summer monsoon rainfall (June through September) and the momentum transport of wave zero TM(0) over latitudinal belt between 25‡S and 5‡N (LB) during March. Northward (Southward) TM(0) observed in March over LB subsequently leads to a good (drought) monsoon season over India which is found to be true even when the year is marked with the El-Nino event. Similarly a strong westerly zone in the Indian Ocean during March, indicates a good monsoon season for the country, even if the year is marked with El-Nino. The study thus suggests two predictors, TM(0) over LB and the strength of westerly zone in the Indian Ocean during March.  相似文献   

Variabilité isotopique des précipitations sahéliennes à différentes échelles de temps à Niamey (Niger) entre 1992 et 1999 : implication climatiqueIsotopic variability of Sahelian rainfall at different time steps in Niamey (Niger, 1992–1999): climatic implications     

Jean-Denis Taupin  Gaëlle Gaultier  Guillaume Favreau  Christian Leduc  Christelle Marlin 《Comptes Rendus Geoscience》2002,334(1):43-50

The isotopic content of rainfall was measured in Niamey (Niger) over a period of eight years (1992–1999). Seasonal distribution of rainy events depends on the monsoon movement over the region. At the beginning and at the end of the rainy season, low rainfall, high temperatures and low relative humidity favour isotopic enrichment. In the middle of the rainy season, heavy rainfall, low temperatures and relative humidity close to saturation lead to isotopically depleted contents because of the mass effect; moreover, in the case of low rainfall, marked vertical convective development favours high altitude condensation. How far the Intertropical Front moves north, determines the quality of the rainy season and influences the isotopic contents. Thus the isotopic contents of rainfall are good climatic indicators. To cite this article: J.-D. Taupin et al., C. R. Geoscience 334 (2002) 43–50  相似文献   

Simulation of artificial random field considering the temporal-spatial variation     

倪永军  朱晞 《地震学报(英文版)》2002,15(4):425-430

Introduction For the seismic design of special structures such as nuclear power station, marine platform, long-span bridge and dam, generally the time-history response analysis of the structure under seismic excitation is imperative, which was coded in most seismic design codes. The earthquake records suitable for the seismic situation and site condition are necessary to be used as the seismic input in the dynamic analysis of structures. As a result of the limited observational condition of st…  相似文献   

Application of genetic BP network to discriminating earthquakes and explosions     

边银菊 《地震学报(英文版)》2002,15(5):540-549

Introduction Artificial Neural Network (ANN) is an important branch of artificial intelligence. It is proposed on the foundation of the study on modern neural science, is a man-made network that can implement some functions based on the mans comprehensive understanding for cerebral neural network (HAN, WANG, 1997). ANN is a mathematical model of simplified human brain neural network and is used to simulate the structures and functions of human brain neural network. ANN is a complex netw…  相似文献   

Vegetation influences on water yields from grassland and shrubland ecosystems in the Chihuahuan Desert     

Mel Neave  Athol D. Abrahams 《地球表面变化过程与地形》2002,27(9):1011-1020

This study examines runoff generated under simulated rainfall on Summerford bajada in the Jornada Basin, New Mexico, USA. Forty‐five simulation experiments were conducted on 1 m² and 2 m² runoff plots on grassland, degraded grassland, shrub and intershrub environments located in grassland and shrubland communities. Average hydrographs generated for each environment show that runoff originates earlier on the vegetated plots than on the unvegetated plots. This early generation of runoff is attributed to soil infiltration rates being overwhelmed by the rapid concentration of water at the base of plants by stemflow. Hydrographs from the degraded grassland and intershrub plots rise continuously throughout the 30 min simulation events indicating that these plots do not achieve equilibrium runoff. This continuously rising form is attributed to the progressive development of raindrop‐induced surface seals. Most grassland and shrub plots level out after the initial early rise indicating equilibrium runoff is achieved. Some shrub plots, however, display a decline in discharge after the early rise. The delayed infiltration of water into macropores beneath shrubs with vegetation in their understories is proposed to explain this declining form. Water yields predicted at the community level indicate that the shrubland sheds 150 per cent more water for a given storm event than the grassland. Copyright © 2002 John Wiley & Sons, Ltd.  相似文献   

ARTIFICIAL NEURAL NETWORK CORRECTION OF ROUGH ERRORS OF OBSERVATIONS^*          下载免费PDF全文

JIANG Guorong  ZHANG Ren  SHA Wenyu  YAN Junyue  YAO Huadong 《Acta Meteorologica Sinica》2002,16(1):123-132

In the context of tower measured radiation datasets.following the correction principle meeting a diagnostic equation in data quality control and in terms of a technique for model construction on data and ANN (artificial neural network) retrieval for BP correction of radiation measurements with rough errors available,a BP model is presented.Evidence suggests that the developed model works well and is superior to a convenient multivariate linear regression model,indicating its wide applications.  相似文献