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91.
Regular aerosol extinction and backscatter measurements using a UV Raman Lidar have been performed for almost 3 years in Hamburg in the frame of the German Lidar Network. A set of 92 aerosol extinction and 164 aerosol backscatter profiles has been used for statistical investigations. Mean values and variances of the aerosol extinction and backscatter in the boundary layer have been calculated. Large fluctuations during the whole year have been found. The measured aerosol extinction over Hamburg shows a seasonal cycle with highest values in early fall and a second less prominent peak in spring.An analysis of the data using back trajectories showed a dependence of the aerosol extinction on the origin of the air mass. The residence time of the air mass over industrialized areas was found to be an important parameter for the measured aerosol extinction at Hamburg. However, only a small part of the total variability could be explained by the air mass origin.For 75 cases of aerosol extinction measurements under cloud-free conditions, the aerosol backscatter profile and therefore, the lidar ratio as a function of altitude could be determined. Winter measurements of the lidar ratio are often close to model results for maritime aerosol, the summer measurements are close to the model results for urban or continental aerosols.The high quality of the data has been proven by intercomparisons with other lidar systems and with star photometer measurements of the aerosol optical depth during the Lindenberg Aerosol Characterization Experiment (LACE'98) field campaign. 相似文献
92.
矿产勘查与评估的统计地球化学方法 总被引:1,自引:0,他引:1
统计地球化学在矿产勘查与评估中的应用,主要包括采术规则,临界品位计算,资源量/储量公式,边界品位确定,网度判别,矿床经济分类以及矿床开发风险等内容。 相似文献
93.
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
94.
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
95.
简单介绍了SAR图像的纹理特征以及正交小波变换纹理提取方法。论述了SAR图像的纹理特征参与分类的重要性。以长白山天池火山为例,通过对ERS2SAR图像进行纹理分析,提取了SAR图像两个层次的尺度变化、时频局部化和方向性纹理特征。并将SAR纹理特征与TM图像及DEM进行复合,利用多源信息各自的优势,进行了BP神经元网络分类,从较大范围对长白山天池火山735±15aB.P.大喷发的喷发物空间分布进行评价。获取了长白山天池火山近代喷发物的空间分布及规模。这对长白山天池火山未来喷发危险性初步评价、火山地质制图及火山灾害预测有重要意义。 相似文献
96.
应用CP网络进行岩性识别 总被引:2,自引:3,他引:2
为通过测井解决岩性识别问题,引入了具有分类准确、算法简练等优点的CP(Counter-Propagation)网络。在详细介绍CP网络的网络模型和算法的基础上,结合某油田的实际测井资料,进行了CP网络识别研究。应用结果表明:CP网络训练周期短、识别准确率高、不存在收敛问题。通过试验研究得出结论:CP网络完全可以用于解决岩性识别等问题,具有广阔的应用前景。 相似文献
97.
98.
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
99.
Introduction The azimuth and slowness are two major features of seismic signals. The accurate estimation of them is quite important for both phase identification and event location. Generally, there are two types of seismic stations, i.e. 3-component stations (3C) and arrays. To estimate the two direc-tional parameters, the polarization analysis (Jurkevics, 1988) is commonly used for 3C stations and the frequency-wavenumber spectrum analysis ( f-k) (Capon, 1969; Kvaerna, Doornbos, 1986) is … 相似文献
100.
Fuzzy neural network models for liquefaction prediction 总被引:1,自引:0,他引:1
Integrated fuzzy neural network models are developed for the assessment of liquefaction potential of a site. The models are trained with large databases of liquefaction case histories. A two-stage training algorithm is used to develop a fuzzy neural network model. In the preliminary training stage, the training case histories are used to determine initial network parameters. In the final training stage, the training case histories are processed one by one to develop membership functions for the network parameters. During the testing phase, input variables are described in linguistic terms such as ‘high’ and ‘low’. The prediction is made in terms of a liquefaction index representing the degree of liquefaction described in fuzzy terms such as ‘highly likely’, ‘likely’, or ‘unlikely’. The results from the model are compared with actual field observations and misclassified cases are identified. The models are found to have good predictive ability and are expected to be very useful for a preliminary evaluation of liquefaction potential of a site for which the input parameters are not well defined. 相似文献