论中国名山的分类

名山分类是山地旅游资源开发的重要理论之一．按成因、属性和功能等不同标准,将中国名山分成地质、气候、历史、文化、政治、军事、揽胜、探险、科考、健身等17个主要类型．     

我国水电地下工程围岩分类系统支护方案探讨

在对我国水电地下工程围岩分类评价系统（ＳＤ系统）和Ｂａｒｔｏｎ的Ｑ系统的分析比较研究的基础上,针对水电工程,探讨了ＳＤ系统和Ｑ系统的相关关系,细化和发展了我国ＳＤ系统的支护设计方案,弥补了其支护类型偏少和简单的不足。     

中国红土型金矿床研究综述

对红土型含矿床的勘查现状,矿化特征及成矿规律进行了探讨和总结,认为它形成于第三系－第四系红土风化壳内,可包括狭义的铁帽型金矿床,;概述了红土型金矿床的有效勘查方法和具体勘查方案。     

灰色聚类与圈闭优选

含油气圈闭系统是一种信息不完全的灰色系统,赖以评价圈闭系统的各项参数的原始获取和定量化过程都具有很大的不确定性,也就是说,这些评价参数都是灰参数,灰色聚类恰恰是解决这种确定性差的多参数评价问题。文中探讨了白化函数的构造方法,指出针对不同约束性能参数,白化参数的构造方式也应区别对待,并提出一种对比隶属函数方法,可以对多个圈闭进行严格的优劣排序,结果令人满意。     

蜥脚类恐龙(Sauropoda)的分类

文章对蜥脚类恐龙的分类进行了探讨,提出了新的分类方案,即将蜥脚类划分为２个超科、７个科。它们分别为勺齿蜥龙超科Ｂｏｔｈｒｏｓａｕｒｏｐｏｄｏｉｄｅａ,包含火山齿龙科Ｖｕｌｃａｎｏｄｏｎ－ｔｉｄａｅ,鲸龙科Ｃｅｔｉｏｓａｕｒｉｄａｅ,腕龙科Ｂｒａｃｈｉｏｓａｕｒｉｄａｅ,圆顶龙科Ｃａｍａｒａｓａｕｒｉｄａｅ和马门溪龙科Ｍａｍｅｎｃｈｉｓａｕｒｉｄａｅ;圆齿蜥龙超科Ｈｏｍａｌｏｓａｕｒｏｐｏｄｏｉｄｅａ,包含梁龙科Ｄｉｐｌｏｄｏｃｉｄａｅ和巨龙科Ｔｉ－ｔａｎｏｓａｕｒｉｄａｅ。     

中国湖泊分类系统研究

应用《近世代数》的商集定义,针对中国湖泊的实际情况,将中国湖泊分成两类、四亚类、八型,初步建立了中国湖泊的分类系统。     

Simulation of the spatio‐temporal extent of groundwater flooding using statistical methods of hydrograph classification and lumped parameter models

This article presents the development of a relatively low cost and rapidly applicable methodology to simulate the spatio‐temporal occurrence of groundwater flooding in chalk catchments. In winter 2000/2001 extreme rainfall resulted in anomalously high groundwater levels and groundwater flooding in many chalk catchments of northern Europe and the southern United Kingdom. Groundwater flooding was extensive and prolonged, occurring in areas where it had not been recently observed and, in places, lasting for 6 months. In many of these catchments, the prediction of groundwater flooding is hindered by the lack of an appropriate tool, such as a distributed groundwater model, or the inability of models to simulate extremes adequately. A set of groundwater hydrographs is simulated using a simple lumped parameter groundwater model. The number of models required is minimized through the classification and grouping of groundwater level time‐series using principal component analysis and cluster analysis. One representative hydrograph is modelled then transposed to other observed hydrographs in the same group by the process of quantile mapping. Time‐variant groundwater level surfaces, generated using the discrete set of modelled hydrographs and river elevation data, are overlain on a digital terrain model to predict the spatial extent of groundwater flooding. The methodology is applied to the Pang and Lambourn catchments in southern England for which monthly groundwater level time‐series exist for 52 observation boreholes covering the period 1975–2004. The results are validated against observed groundwater flood extent data obtained from aerial surveys and field mapping. The method is shown to simulate the spatial and temporal occurrence of flooding during the 2000/2001 flood event accurately. British Geological Survey © NERC 2011. Hydrological Processes © 2011 John Wiley & Sons, Ltd.     

Detecting Arctic snow and ice cover with FY-1D global data

Chinese meteorological satellite FY-1D can obtain global data from four spectral channels which include visible channel(0.58-0.68 μm) and infrared channels(0.84-0.89 μm,10.3-11.3 μm,11.5-12.5 μm).2366 snow and ice samples,2024 cloud samples,1602 land samples and 1648 water samples were selected randomly from Arctic imageries.Land and water can be detected by spectral features.Snow-ice and cloud can be classified by textural features.The classifier is Bayes classifier.By synthesizing five d ays classifying result of Arctic snow and ice cover area,complete Arctic snow and ice cover area can be obtained.The result agrees with NOAA/NESDIS IMS products up to 70%.     

A New Feature Vector Using Selected Line Spectra for Pulsar Signal Bispectrum Characteristic Analysis and Recognition

Average pulse profiles of pulsar signals are analyzed using the bispectrum tech-nique. The result shows that there are nonlinear phase couplings between the two frequency axes of the bispectrum charts, which indicate nonlinear factors in the generation and prop-agation of pulsar signals. Bispectra can be used as feature vectors of pulsar signals because of their being translation invariant. A one-dimension selected line spectrum algorithm for ex-tracting pulsar signal characteristic is proposed. Compared with selected bispectra, the pro-posed selected line spectra have the maximum interclass separability measurements from the point of view of the whole one-dimension feature vector. Recognition experiments on several pulsar signals received at several frequency bands are carried out. The result shows that the selected line spectrum algorithm is suitable for extracting pulsar signal characteristics and has a good classification performance.     

基于模糊Hopfield神经网络的大气降水粒子分类

提出基于模糊Hopfield神经网络的大气降水粒子分类,它是通过计算样本间的模糊关系的相似程度,再加上Hopfield网络所特有的高稳定性,对大气降水粒子进行分类.通过对各降水粒子所对应雷达回波数据的分析,验证了方法的可行性.