灰色聚类法在常州市第Ⅱ承压地下水水质评价中的应用

在灰色聚类方法原理的基础上，探讨了如何通过白化函数生成灰色聚类矩阵，并以常州市第Ⅱ承压地下水为例进行了水质评价，评价结果表明，常州市大部分第Ⅱ承压地下水水质优良，达到了Ⅰ类水，未遭受外来物质的污染，评价结果符合实际情况。     

数据挖掘技术在水文预报中的应用及水文预报发展趋势研究

数据挖掘作为知识发现过程中的重要步骤,是从大型数据库中提取未知的、有价值的和可操作性的关系、模式和趋势用于决策支持的过程。我国目前在防洪领域存在着大量水文数据,如何充分有效地利用各种智能算法对这些数据进行分析与挖掘,以形成相应的水文预报模型进行准确的水文预报是防洪决策支持系统完善和发展的重要方面。本文首先全面地介绍数据挖掘的功能分类及以数据挖掘为基础的水文预报体系,然后对数据挖掘技术在水文预报中的应用进行了探讨和研究。     

Road Surface Modeling and Representation from Point Cloud Based on Fuzzy Clustering

A scheme for an automatic road surface modeling from a noisy point cloud is presented. The normal vectors of the point cloud are estimated by distance-weighted fitting of local plane. Then, an automati...     

资源卫星（可见光）遥感数据获取任务调度优化算法研究

从资源卫星（可见光）遥感数据获取任务调度的影响因子分析入手,在研究国外相关遥感任务调度算法的基础上,提出了基于目标的卫星遥感任务调度算法规则,并依据该规则研究建立了算法实现流程,以解决用户需求和星地资源使用约束之间的冲突,从而有效地满足用户对遥感数据的需求。     

Clustering stochastic point process model for flood risk analysis

Since the introduction into flood risk analysis, the partial duration series method has gained increasing acceptance as an appealing alternative to the annual maximum series method. However, when the base flow is low, there is clustering in the flood peak or flow volume point process. In this case, the general stochastic point process model is not suitable to risk analysis. Therefore, two types of models for flood risk analysis are derived on the basis of clustering stochastic point process theory in this paper. The most remarkable characteristic of these models is that the flood risk is considered directly within the time domain. The acceptability of different models are also discussed with the combination of the flood peak counted process in twenty years at Yichang station on the Yangtze river. The result shows that the two kinds of models are suitable ones for flood risk analysis, which are more flexible compared with the traditional flood risk models derived on the basis of annual maximum series method or the general stochastic point process theory. Received: September 29, 1997     

湖泊富营养化灰色聚类评价及几种评价法比较

本文把湖泊营养化系统看作一个灰色系统,应用灰色聚类法进行营养化评价,并通过实例和层次决策法,Fuzzy-Greey决策法的评价结果进行分析与比较。     

A fuzzy dynamic flood routing model for natural channels

A fuzzy dynamic flood routing model (FDFRM) for natural channels is presented, wherein the flood wave can be approximated to a monoclinal wave. This study is based on modification of an earlier published work by the same authors, where the nature of the wave was of gravity type. Momentum equation of the dynamic wave model is replaced by a fuzzy rule based model, while retaining the continuity equation in its complete form. Hence, the FDFRM gets rid of the assumptions associated with the momentum equation. Also, it overcomes the necessity of calculating friction slope (S_f) in flood routing and hence the associated uncertainties are eliminated. The fuzzy rule based model is developed on an equation for wave velocity, which is obtained in terms of discontinuities in the gradient of flow parameters. The channel reach is divided into a number of approximately uniform sub‐reaches. Training set required for development of the fuzzy rule based model for each sub‐reach is obtained from discharge‐area relationship at its mean section. For highly heterogeneous sub‐reaches, optimized fuzzy rule based models are obtained by means of a neuro‐fuzzy algorithm. For demonstration, the FDFRM is applied to flood routing problems in a fictitious channel with single uniform reach, in a fictitious channel with two uniform sub‐reaches and also in a natural channel with a number of approximately uniform sub‐reaches. It is observed that in cases of the fictitious channels, the FDFRM outputs match well with those of an implicit numerical model (INM), which solves the dynamic wave equations using an implicit numerical scheme. For the natural channel, the FDFRM outputs are comparable to those of the HEC‐RAS model. Copyright © 2009 John Wiley & Sons, Ltd.     

Accelerating the convergence of coupled geomechanical‐reservoir simulations

The pressure variations during the production of petroleum reservoir induce stress changes in and around the reservoir. Such changes of the stress state can induce marked deformation of geological structures for stress sensitive reservoirs as chalk or unconsolidated sand reservoirs. The compaction of those reservoirs during depletion affects the pressure field and so the reservoir productivity. Therefore, the evaluation of the geomechanical effects requires to solve in a coupling way the geomechanical problem and the reservoir multiphase fluid flow problem. In this paper, we formulate the coupled geomechanical‐reservoir problem as a non‐linear fixed point problem and improve the resolution of the coupling problem by comparing in terms of robustness and convergence different algorithms. We study two accelerated algorithms which are much more robust and faster than the conventional staggered algorithm and we conclude that they should be used for the iterative resolution of coupled reservoir‐geomechanical problem. Copyright © 2006 John Wiley & Sons, Ltd.     

基于稀疏AR模型的潮流信号建模与预报

潮流信号处理与预报在很多方面具有非常重要的意义和价值。本文引入信号稀疏表示理论,构建一种稀疏AR模型,寻找各潮流数据间的历史关联性,并进行预报分析。首先由实测潮流信号进行常规AR建模,获得一组过完备稀疏基;其次随机从该过完备稀疏基抽取部分建立欠定方程组,利用稀疏优化算法获得最稀疏的AR系数;多次重复上一步,获得稀疏AR系数的平均以增强稀疏AR模型的稳定性;最后利用这些稀疏AR系数来重构或预测潮流信号。文章针对实测潮流信号,特别是存在多峰值有回流现象的潮流信号,进行了稀疏AR建模与预测的多次实验。实验结果与传统的潮流信号调和预报方法相对比,发现基于稀疏AR模型的潮流预报对于潮流存在多变的现象时,具有明显优越性,从回报结果来看,稀疏AR模型的潮流预报均方差明显小于传统潮流调和分析预报方法。