Uncertainties in real‐time flood forecasting with neural networks

Although artificial neural networks (ANNs) have been applied in rainfall runoff modelling for many years, there are still many important issues unsolved that have prevented this powerful non‐linear tool from wide applications in operational flood forecasting activities. This paper describes three ANN configurations and it is found that a dedicated ANN for each lead‐time step has the best performance and a multiple output form has the worst result. The most popular form with multiple inputs and single output has the average performance. In comparison with a linear transfer function (TF) model, it is found that ANN models are uncompetitive against the TF model in short‐range predictions and should not be used in operational flood forecasting owing to their complicated calibration process. For longer range predictions, ANN models have an improved chance to perform better than the TF model; however, this is highly dependent on the training data arrangement and there are undesirable uncertainties involved, as demonstrated by bootstrap analysis in the study. To tackle the uncertainty issue, two novel approaches are proposed: distance analysis and response analysis. Instead of discarding the training data after the model's calibration, the data should be retained as an integral part of the model during its prediction stage and the uncertainty for each prediction could be judged in real time by measuring the distances against the training data. The response analysis is based on an extension of the traditional unit hydrograph concept and has a very useful potential to reveal the hydrological characteristics of ANN models, hence improving user confidence in using them in real time. Copyright © 2006 John Wiley & Sons, Ltd.     

腾冲火山区某些地震学参数特征

测定了腾冲火山区地震震中位置和震源深度,对火山区及附近的震源深度、地震时距曲线和地震波速度等地震学参数特征作了分析。结果表明,腾冲火山区地震震源深度相对较小,向周围地区逐渐增大,震源深度分布的低值区,又是环境剪应力场的值分布区。腾冲火山区Ｐ、Ｓ波平均速度,明显比外围地区小,腾冲火山区存在低速区。这些地震学参数分布的差异,一方面反映出地区作为火山区的固有特征及其地域分布的大小,同时也揭示出腾冲火山在     

光电测距仪短距测量精度的实验性评价

对目前国内常见的一些光电测距仪的短距测量精度进行了实际测试。测试结果表明任何一台工作性能正常、标称精度等于或优于± (5mm 5× 10 -6D)的测距仪 ,在2 0 0m范围内其测距精度优于 3 0mm、在 15 0m范围内优于 2 3mm、在 10 0m范围内优于1 2mm、在 5 0m范围内优于 0 9mm。     

Distance predicting functions and applied location-allocation models.

Distances between demand points and potential sites for implementing facilities are essential inputs to location-allocation models. Computing actual road distances for a given problem can be quite burdensome since it involves digitalizing a network, while approximating these distances by l _p -norms, using for instance a geographical information system, is much easier. We may then wonder how sensitive the solutions of a location-allocation model are to the choice of a particular metric. In this paper, simulations are performed on a lattice of 225 points using the k-median problem. Systematic changes in p and in the orientation of the orthogonal reference axes are used. Results suggest that the solutions of the k-median are rather insensitive to the specification of the l _p -norm. Received: 12 October 1998/Accepted: 17 September 1999     

Diurnal variation of urban structure in terms of time distance: A spatio-temporal analysis of an urban area

The purpose of this paper is to clarify the diurnal variations in structure of an urban area from the viewpoint of time distance. To accomplish this, for one entire day, and for the morning, noon, and evening periods, time maps are delineated by using MDS; also, the indices of accessibility and circuity are computed from the time distances. As a result, the difference in shape between the time and actual maps becomes clear especially in the morning and also in the evening. Both the accessibility and circuity measured from the time distance show a concentrically shaped pattern where the regional disparity is especially distinct within the morning and evening periods. The diurnal variations as described above are thought to occur against the backdrop of the topological traffic conditions within the study area. This revised version was published online in July 2006 with corrections to the Cover Date.     

Logratio Analysis and Compositional Distance

The concept of distance between two compositions is important in the statistical analysis of compositional data, particularly in such activities as cluster analysis and multidimensional scaling. This paper exposes the fallacies in a recent criticism of logratio-based distance measures—in particular, the misstatements that logratio methods destroy distance structures and are denominator dependent. Emphasis is on ensuring that compositional data analysis involving distance concepts satisfies certain logically necessary invariance conditions. Logratio analysis and its associated distance measures satisfy these conditions.     

按运动学方法确定疏散星团M11的距离

在合理假设星团成员星的内部随机运动为各向同性的基础上,提出一种利用纯运动学资料确定星团距离的方法,并依此方法估算出疏散星团M11的速度距离为(1．89±0．52)kpc。这一结果与其他作者给出的星团M11的光度距离符合得相当好。