Multicollinearity and correlation among local regression coefficients in geographically weighted regression

Present methodological research on geographically weighted regression (GWR) focuses primarily on extensions of the basic GWR model, while ignoring well-established diagnostics tests commonly used in standard global regression analysis. This paper investigates multicollinearity issues surrounding the local GWR coefficients at a single location and the overall correlation between GWR coefficients associated with two different exogenous variables. Results indicate that the local regression coefficients are potentially collinear even if the underlying exogenous variables in the data generating process are uncorrelated. Based on these findings, applied GWR research should practice caution in substantively interpreting the spatial patterns of local GWR coefficients. An empirical disease-mapping example is used to motivate the GWR multicollinearity problem. Controlled experiments are performed to systematically explore coefficient dependency issues in GWR. These experiments specify global models that use eigenvectors from a spatial link matrix as exogenous variables.This study was supported by grant number 1 R1 CA95982-01, Geographic-Based Research in Cancer Control and Epidermiology, from the National Cancer Institute. The author thank the anonymous reviewers and the editor for their helpful comments.     

Hyper Redundancy for Accuracy Enhancement in Automated Close Range Photogrammetry

A generic network design in close range photogrammetry is one where optimal multi-ray intersection geometry is obtained with as few camera stations as practicable. Hyper redundancy is a concept whereby, once the generic network is in place, many additional images are recorded, with the beneficial impact upon object point precision being equivalent to the presence of multiple exposures at each camera position within the generic network. The effective number of images per station within a hyper redundant network might well be in the range of 10 to 20 or more. As is apparent when it is considered that a hyper redundant network may comprise hundreds of images, the concept is only applicable in practice to fully automatic vision metrology systems, where it proves to be a very effective means of enhancing measurement accuracy at the cost of minimal additional work in the image recording phase. This paper briefly reviews the network design and accuracy aspects of hyper redundancy and illustrates the technique by way of the photogrammetric measurement of surface deformation of a radio telescope of 26 m diameter. This project required an object point measurement accuracy of σ  = 0·065 mm, or 1/400 000 of the diameter of the reflector.     

对江西农经网如何更好地提供信息服务的探讨

分析了江西农村经济信息网(www.jxagriec.gov.cn)的现状,指出农经网信息服务正面临着挑战,并在此基础上阐述了农经网信息服务的发展思路。     

广西新一代"区-地-县"三级气象信息网络系统

介绍广西新一代“区 -地 -县”三级气象信息网络系统在拓扑结构、业务软件和运行管理等方面的基本情况 ,总结了建设、运行管理过程中成功经验以及存在的问题 ,指出 :充分利用现有通讯网络资源 ,强化业务软件的开发应用 ,提高网络传输监控管理水平 ,是经济欠发达地区扩展气象信息网络业务能力的重要途径     

Structure Functions In A Wall-Turbulent Shear Flow

Wavelet and quadrant analyses were applied to turbulent velocity data in order to investigate the transition from the anisotropy of energy-containing eddies to the isotropy of the inertial subrange scales. The quadrant analysis of the wavelet coefficients of longitudinal and vertical velocity components allows the evaluation of the velocity structure functions and the momentum cospectrum as a function of the separation distance and of the quadrants. In an isotropic condition the contribution both of ejections and sweeps (even quadrants), and both of reflections and deflections (odd quadrants), has to be equal. The analysis has shown that in neutrally stratified conditions the transition to isotropy occurs in a frequency range (0.2 < r/z < 3) usually referred to as internal to the inertial subrange (r is separation distance, z is height). In the transition region, as in the isotropic region, the velocity structure functions still agree with the 1941 and 1962 Kolmogorov theories; but on the other hand the structure functions of the even and odd quadrants are fitted by power laws of different slopes in the transition region. The proposed analysis allows the investigation within the transition region of the different dynamical structure in the energy transfer from the energy-containing scales to the isotropic scales.     

矿产勘查与评估的统计地球化学方法

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。     

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

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.     

Modelling evaporation using an artificial neural network algorithm

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.     

利用ERS-2 SAR图像纹理分析方法揭示长白山天池火山近代喷发物空间分布特征

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。     

应用CP网络进行岩性识别

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。