从受训神经-模糊模型中提取知识

本文对用于模式分类、函数逼近、参数估计的多层感知器 (MLPs)给出 1个清晰的关于内部行为的解释。作者以单隐层的 MLP为例 ,论述了关于 MLP的内部行为的半线性分析理论。对受训的MLP,将隐层单元的输出分别定义为网络输出的正、负“内部分量”;定义内部分量的连接权重集为给定问题的“内部判别模式”;建立了 MLP和模糊集相结合的新模型 ;分析了 MLP的结构为 N- 2 - 1和N- H- 1 ,给出权重初始化的方法 ;提出了 1种从受训神经 -模糊模型 (NFMs)中提取知识的全新的具有实用价值的方法。     

基于模糊综合评判理论的过驳系统效率计算方法

如何计算整个系统的运转效率，特别是受不确定因素影响的系统(如过驳系统)，仍然是一个非常重要的研究课题。文章提出基于模糊综合评判方法的效率计算方法，是一种新的尝试，这种方法较好的避免了人的主观随意性，更符合实际情况，同时又可以弥补统计方法的不足。文章对某沿海地区的一过驳系统进行了效率计算，取得比较好的效果。     

一种基于启发式算法的等高线局部内插方法

在基于启发式内插等高线算法的基础上提出了一种局部内插方法。首先利用Douglas-Peucker算法提取等高线的特征点,根据特征点判断等高线之间的相似性程度,找出导致等高线出现异常的特征点;然后将相似性程度很低的两条等高线自动分解为若干简单等高线再进行内插。有效地解决了局部弯曲很大、马鞍型地貌等复杂等高线的内插问题。算法已经在以Microstation为平台的数字制图系统中实现并逐渐实用化。     

基于边优先的任意多边形最优三角剖分

针对现有多边形三角剖分算法不能同时兼顾算法的简单有效性、适用性以及剖分三角网质量的问题,提出一种基于边优先的任意多边形最优化三角剖分算法:首先直接对多边形的边进行构网,最后再对生成的非约束边进行构网,最终完成整个多边形的三角剖分。剖分得到的三角网为约束Delaunay三角网,网形稳定、最优,算法简单,执行效率较高,且适用于任意复杂多边形。实验证明了该算法的合理性和有效性,较好地解决了现有多边形三角剖分算法存在的问题。     

GIS空间关联规则挖掘研究

提取不同对象或现象间相互联系的空间规律,发现、解释或预测空间现象或事件,是GIS空间关联规则挖掘价值的体现。通过对目前的空间关联规则挖掘理论和实例的研究,分析了挖掘过程涉及到的基本问题：挖掘实施的基本步骤、开发路线、挖掘有效性的保证,挖掘方法及优化策略等,得到了实用的挖掘的一般方法,也对挖掘的应用实例进行了分析,展望了应用前景。     

城市综合地下管线普查全过程监理技术方法

针对城市综合地下管线普查全过程监理的应用问题,着重探讨全过程监理的总体思路、组织架构与制度保障,进而给出地下管线普查各阶段监理的技术方法与实施要点。     

TM影像几何校正算法的精度比较

同大多数的线阵推扫式影像相比,TM影像作为双向扫描型的影像其几何校正方法有其特殊性和复杂性。针对这个问题,本文简要介绍了一般多项式、空间斜墨卡托投影、有理函数模型等几种几何近似校正算法,并利用广州地区的TM影像进行了各种试验分析和精度比较。结果表明:同其他方法相比,空间斜墨卡托投影是一种较好的算法,校正精度最高,能够达到一个像素左右,而且该方法不受地形起伏的影响,无需地面高程信息。     

X-ray spectroscopy of stellar coronae

Summary From the early discovery in 1948 of X-rays from the Solar corona, X-ray spectroscopy has proven to be an invaluable tool in studying hot astrophysical and laboratory plasmas. Because the emission line spectra and continua from optically thin plasmas are fairly well known, high-resolution X-ray spectroscopy has its most obvious application in the measurement of optically thin sources such as the coronae of stars. In particular X-ray observations with theEINSTEIN observatory have demonstrated that soft X-ray emitting coronae are a common feature among stars on the cool side of the Hertzsprung-Russell diagram, with the probable exception of single very cool giant and supergiant stars and A-type dwarfs. Observations with the spectrometers aboardEINSTEIN andEXOSAT have shown that data of even modest spectral resolution (/ = 10–100) permit the identification of coronal material at different temperatures whose existence may relate to a range of possible magnetic loop structures in the hot outer atmospheres of these stars. The higher spectral resolution of the next generation of spectrometers aboard NASA'sAXAF and ESA'sXMM will allow to fully resolve the coronal temperature structure and to enable velocity diagnostics and the determination of coronal densities, from which the loop geometry (i.e. surface filling factors and loop lengths) can be derived. In this paper various diagnostic techniques are reviewed and the spectral results fromEINSTEIN andEXOSAT are discussed. A number of spectral simulations forAXAF andXMM, especially high-resolution iron K-shell, L-shell, and2s-2p spectra in the wavelength regions around 1.9 Å, 10 Å, and 100 Å, respectively, are shown to demonstrate the capabilities for temperature, density, and velocity diagnostics. Finally, iron K-shell spectra are simulated for various types of detectors such as microcalorimeter, Nb-junction, and CCD.     

A Decision Support System for the Evaluation of Eco-engineering Strategies for Slope Protection

A decision support system (DSS) has been developed to assist expert and non-expert users in the evaluation and selection of eco-engineering strategies for slope protection. This DSS combines a qualitative hazard assessment of erosion and mass movements with a detailed catalogue of eco-engineering strategies for slope protection of which the suitability is evaluated in relation to the data entered. The slope decision support system (SDSS) is a knowledge based DSS in which knowledge is stored in frames containing rules that can evaluate the available information for a project, stored as project specific information (PSI) in a data file. The advantages of such a system are that it accepts incomplete information and that the qualitative nature of the information does not instil the user with a sense of unjustified exactitude. By its multidisciplinary and progressive nature, the DSS will be of value during the initial stages of an eco-engineering project when data collection and the potential of different eco-engineering strategies are considered. The accent of the output of the DSS is on the application of eco-engineering strategies for slope protection as an environmentally-friendly solution aiding sustainable development. For its acceptance within the engineering community, the DSS needs to prove its predictive capacity. Therefore, its performance has been benchmarked against successful and unsuccessful cases of slope stabilisation using eco-engineering. The target audience and the areas of application of this DSS are reviewed and the strategies for further development in this area suggested.