Classification of artificial (man-made) ground   总被引：1，自引：0，他引：1  

M. S. Rosenbaum  A. A. McMillan  J. H. Powell  A. H. Cooper  M. G. Culshaw  K. J. Northmore 《Engineering Geology》2003,69(3-4):399-409

The legacy inherited from anthropogenic processes needs to be addressed in order to provide reliable and up-to-date ground information relevant to development and regeneration in the urban environment. The legacy includes voids as well as anthropogenic deposits (artificial ground). Their characteristics derive from former quarrying and mining activities industrial processes creating derelict ground, variably consolidated made ground, and contaminated groundwater and soils. All need to be systematically assessed to inform the planning process and provide the basis for engineering solutions. Site-specific investigation needs to be conducted on the back of good quality geoscientific data. This comes from ‘field’ survey, remotely sensed data interpretation, historical maps, soil geochemical sampling, and geotechnical investigation. Three-dimensional and, in the future, four dimensional, characterization of superficial deposits is required to reach an understanding of the potential spatial lithological variability of artificial ground and the geometry of important surfaces, i.e. the boundary conditions. The classification scheme for artificial ground outlined in this paper and adopted by the British Geological Survey, will help in achieving this understanding.  相似文献   

Application of visual,statistical and artificial neural network methods in the differentiation of water from the exploited aquifers in Kuwait     

Amitabha Mukhopadhyay 《Hydrogeology Journal》2003,11(3):343-356

The ability of artificial neural network to differentiate water samples from the two aquifers of Kuwait on the basis of their major ion chemistry has been demonstrated. The major ion concentration distribution in the groundwater of the Kuwait Group and the Dammam Formation aquifers of Kuwait appears very similar. Cross-plots, supported by the discriminant function analysis of the data, however, suggest that there are some subtle differences in the overall composition of the water from the two aquifers that make it possible to differentiate the water from the two aquifers in almost 80% of the cases. An artificial neural network improved the differentiation capability to 90% of the cases. It is also possible to estimate the fraction of Kuwait Group water in the flow stream of dually completed wells with the help of an artificial neural network developed for this purpose. Electronic Publication  相似文献   

福建省干旱概况及夏旱期间人工增雨条件分析   总被引：3，自引：1，他引：3  

夏丽花冯玲  曾光平 《应用气象学报》2003,14(Z1):143-150

对福建省干旱的成因和干旱的环流形势进行了探讨,着重分析了夏旱期间人工增雨作业的天气形势、云状、回波特征及云顶温度等条件,结果表明福建省干旱的形成与大型环流形势、地形、地貌及土壤植被条件有关;平均而言,闽东南沿海干旱多于内陆地区;西太平洋副热带高压是夏季致旱的主要天气系统;夏季,西风槽前型、台风外围影响型、副热带辐合带型是进行人工增雨作业的有利天气形势,Sc、Cb、Cu云都有一定的人工增雨作业条件,其中降水时长1～5 h,过程雨量1.0～5.0 mm的云是旱季作业比较适合的作业云.这些结果为开展人工增雨作业提供理论依据,达到解除或缓解干旱的目的.  相似文献   

神经网络技术在地面沉降区划中的应用研究   总被引：1，自引：2，他引：1  

武建强  余勤 《江苏地质》2003,27(3):171-174

复杂的第四系沉积环境构成地面沉降的地质背景，在对比分析第四系厚度、地下水位、含水层以及软土层发育程度的基础上，尝试性地运用人工神经网络技术对苏锡常地区地面沉降易发区进行识别。除基岩出露区外全区共被划分成4类块段，这种分布与第四系条件具有很强的空间相关性，经检验具有较高的可信度。  相似文献   

红板岩材料隐式本构模型的建立及其应用研究     

邹光华  朱建明 《工程地质学报》2003,11(3):258-262

针对红板岩材料在岩土工程中所表现的大量模糊的和不确定的因素等特点,基于人工神经网络的学习能力,借助于室内岩石力学试验,进行了对该材料的力学本构特性进行了神经网络模拟研究,提出了隐式本构模型的思想和方法,并通过该方法对该岩石的流变试验结果进行学习,获得了以网络权值结构保存的力学特性知识,由此得到了表征红板岩应力应变本构关系的隐式本构模型。应用结果表明,该方法对岩土类材料本构关系的模拟研究具有很好的应用前景。  相似文献   

An Artificial Intelligent design for GPS Surveying Networks     

Hussain?Aziz?SalehEmail author 《GPS Solutions》2003,7(2):101-108

Metaheuristic techniques, which are based on ideas of Artificial Intelligence, are among the best methods for solving computationally the GPS surveying network problem. In this paper, the ant colony optimization metaheuristic, which is inspired by the behavior of real ant colonies, is developed to efficiently provide a general framework for optimizing GPS surveying networks. In this framework, a set of ants co-operate together using an indirect communication procedure to find good GPS observation schedules. A GPS surveying network can be defined as a set of stations, co-ordinated by a series of sessions formed by placing receivers on the stations. The problem is to search for the best order in which to observe these sessions to give the best schedule at minimum cost. Computational results obtained by applying the proposed technique on several networks, with known and unknown optimal schedules, prove the effectiveness of the proposed metaheuristic technique to solve the GPS surveying network problem.  相似文献   

Biomonitoring of coastal pollution status using protozoan communities with a modified PFU method   总被引：10，自引：0，他引：10  

Xu K  Choi JK  Yang EJ  Lee KC  Lei Y 《Marine pollution bulletin》2002,44(9):877-886

Structural and functional parameters of protozoan communities were assessed as indicators of water quality in Korean coastal waters in the summer of 2000. A modified polyurethane foam unit (PFU) method, named the bottled PFU (BPFU) system, was used in order to carry out the bioassessment. Both parameters suggested that biomonitoring using the BPFU system was more effective than the conventional PFU method in offshore areas. The species number collected by the BPFU system generally decreased as pollution intensity increased at three main stations and was greater than that collected using the PFU method (paired t-test, t = 4.83, p < 0.0001). The Margalef diversity index coincided well with the water conditions. The diversity index values calculated from the BPFU system were also significantly higher than those from the PFU method (paired t-test, t = 5.37, p < 0.0001). Furthermore, the functional parameters, i.e. S(eq),G and T90%, correlated with the pollution status and could thus clearly discriminate the different classes of water quality.  相似文献   

Prediction of creep characteristic of rock under varying environment   总被引：2，自引：0，他引：2  

T. N. Singh  A. K. Verma 《Environmental Geology》2005,48(4-5):559-568

The strain developed due to creep is mainly proportional to the logarithm of the time under load, and is mostly proportional to the stress and temperature. At higher temperature the creep rate falls slowly with respect to time, and the creep strain is proportional to a fractional power of time, with the exponent increasing as the temperature increases and reaching a value approximately one-third at temperatures of about 0.5°C. At these temperatures, the creep increases with stress according to a power greater than unity and possibly exponentially. It increases with temperature as (−U/kT), where U is an activation energy and k is Boltzman’s constant. There are different methods to determine the creep strain and the energy of Jog (B) including experimental methods, multivariate regression analysis, and by numerical simulation. These methods are less cumbersome and time consuming. In the present investigation, artificial neural network technique has been used for prediction of the creep strain and energy of Jog (B). Two different networks have been tested and validated. Both the networks have four input neurons and one hidden layer with five neurons, and one output neuron. The data for different rocks at temperatures up to 750°C under conditions of compressive or tortional stress are taken from the literatures. The training and testing data sets used were 163 and 14, respectively. To deal with the problem of overfitting of data, Bayesian regulation has been used and network is trained with suitable training epochs. The coefficients of correlation among the predicted and observed values are found high and they improve the confidence of the users. The mean absolute percentage error obtained are also very low.  相似文献   

Determination and application of the weights for landslide susceptibility mapping using an artificial neural network   总被引：38，自引：0，他引：38  

Saro Lee  Joo-Hyung Ryu  Joong-Sun Won  Hyuck-Jin Park 《Engineering Geology》2004,71(3-4):289-302

The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.  相似文献   

探索地理信息智能化处理技术     

黄继安  史照良 《现代测绘》2004,27(2):9-12

GIS自产生至今30多年来，世界各国都竞相开展GIS技术研究和应用开发，使其得到了迅速的发展，已形成较为完整的理论体系和大批实用系统，并已在社会各专业领域得到广泛应用并产生了巨大效益，目前，开始朝着产业化、集成化、智能化和社会化的方向发展。随着3S技术的集成应用，人们对GIS的运行效率及其深入的应用提出了更高的要求，地理信息智能化处理已成为地图学和GIS建设必须解决的问题，也是GIS发展的必然方向。在地理信息处理中采用人工智能技术，发展智能GIS或者专家GIS，是解决复杂地学问题的重要途径，也是目前GIS最吸引人的一个应用方向。目前在地理信息处理的许多领域都在使用人工智能技术，比如地图模式识别、地理数据的自动分类、地学专家系统、智能GIS、空间数据挖掘等。本文通过对当前地理信息智能化处理技术发展现状的阐述，旨在探索人工智能在地理信息处理中的应用前景。  相似文献