Modelling evaporation using an artificial neural network algorithm

This paper investigates the prediction of Class A pan evaporation using the artificial neural network (ANN) technique. The ANN back propagation algorithm has been evaluated for its applicability for predicting evaporation from minimum climatic data. Four combinations of input data were considered and the resulting values of evaporation were analysed and compared with those of existing models. The results from this study suggest that the neural computing technique could be employed successfully in modelling the evaporation process from the available climatic data set. However, an analysis of the residuals from the ANN models developed revealed that the models showed significant error in predictions during the validation, implying loss of generalization properties of ANN models unless trained carefully. The study indicated that evaporation values could be reasonably estimated using temperature data only through the ANN technique. This would be of much use in instances where data availability is limited. Copyright © 2002 John Wiley & Sons, Ltd.     

公路边坡工程监测技术评价与分析

结合公路工程、建筑工程等土木工程建设中经常涉及到的边坡工程,评价与分析边坡工程监测的作用、内容和方法,提出了边坡工程应该在工程项目开展的开始阶段就应进行和边坡工程监测的项目,选择原则,测点布置原则、监测周期等,对边坡工程建设具有重要的意义.     

利用ERS-2 SAR图像纹理分析方法揭示长白山天池火山近代喷发物空间分布特征

简单介绍了SAR图像的纹理特征以及正交小波变换纹理提取方法。论述了SAR图像的纹理特征参与分类的重要性。以长白山天池火山为例,通过对ERS2SAR图像进行纹理分析,提取了SAR图像两个层次的尺度变化、时频局部化和方向性纹理特征。并将SAR纹理特征与TM图像及DEM进行复合,利用多源信息各自的优势,进行了BP神经元网络分类,从较大范围对长白山天池火山735±15aB.P.大喷发的喷发物空间分布进行评价。获取了长白山天池火山近代喷发物的空间分布及规模。这对长白山天池火山未来喷发危险性初步评价、火山地质制图及火山灾害预测有重要意义。     

EFG法在土体固结中的应用

EFGM作为一种新的数值计算方法，具有只需节点信息而无段单元的特性，故在解固结方程方面有很大的优势。在计算分析中，此法容易构造固结方程的EFGM刚度矩阵和处理不同边界条件。对单面排水等条件的计算结果表明，EFGM在解决固结变形问题上，精度较高，处理边界准确。     

应用CP网络进行岩性识别

为通过测井解决岩性识别问题，引入了具有分类准确、算法简练等优点的CP（Counter-Propagation)网络。在详细介绍CP网络的网络模型和算法的基础上，结合某油田的实际测井资料，进行了CP网络识别研究。应用结果表明：CP网络训练周期短、识别准确率高、不存在收敛问题。通过试验研究得出结论：CP网络完全可以用于解决岩性识别等问题，具有广阔的应用前景。     

Analyzing CO2 emissions mitigation by technology improvement in Central and Eastern Europe

As a legacy of the centrally planned economy, the economies in transition of Central and Eastern Europe (CEE) have a unique potential to reduce their greenhouse gas emissions through the improvement in their high energy intensities. Since much of this `low-hanging fruit' in energy-efficiency improvements can be highly cost-effective, many developed countries facing difficulties in meeting their greenhouse gas (GHG) emission targets domestically are eager to find such opportunities in the CEE region. Therefore, studies analysing the potentials and costs of carbon dioxide reduction through technology improvement in the region have come into the limelight. While there are a few excellent studies in the region aimed at analysing climate change abatement potentials, they all embark on different assumptions, methodologies and boundary conditions. It is hence difficult, if not impossible, to compare and analyse the results of these studies across different authors, countries or time horizons. Consequently, the purpose of this paper is to place four leading studies on GHG mitigation through technology improvement from the CEE region into an internationally comparable framework. Four studies were selected from three countries, Poland, Hungary and Estonia, which are all the results of major national and international efforts to assess costs and potentials of GHG reduction. The paper places their assumptions, methods and final results into a framework which enables policy-makers and project designers to compare these across geographical and technological boundaries. Since other studies from around the globe have been analysed in this framework in the literature, this paper provides a vehicle for the findings of these four studies to be compared to others worldwide. In addition, the paper highlights a few areas where similar studies to be completed in the future in the region may be enhanced by incorporating features used in GHG mitigation research in other parts of the world. This revised version was published online in July 2006 with corrections to the Cover Date.     

数字遥测地震台网地震速报中文平台

叙述了数字遥测地震台网地震速报中平台程序基本流程和使用特点，程序采用Vi编程方法实现以二维坐标点阵结构显示汉字，与台网的交互软件（EDSP-IAS）中的WaveView程序自动链接运行，该闰台界面操作方便直观，易于定位地震参数，自动速报上网和自动寻呼。     

基于ODBC的地震前兆数据批量卸出与转换程序的实现

介绍了CDBC技术、工作流程及数据传递方式；分析了研制数据卸出与转换程序的关键技术及实现方法；描述了程序的组织结构。通过实例说明了该程序在全国前兆台网中心卸载与转换地震前兆数字化的观测数据中的应用。     

福建漳州、华安、龙岩地区地震时间分布结构信息维的特征

岩石破裂实验，地球岩石层断裂构造运动，地震孕育、发生和发展过程等研究表明，地震活动的时间、空间和强度分布特征具有分形结构。作为一种分维理论的应用，本文利用厦门数字化地震遥测台网的数据，采用信息的分析方法，对福建省的地震多发区-漳州、华安、龙岩地区的地震活动进行了分析和研究，讨论了信息维随时间变化的特征。     

Application of genetic BP network to discriminating earthquakes and explosions

Introduction Artificial Neural Network (ANN) is an important branch of artificial intelligence. It is proposed on the foundation of the study on modern neural science, is a man-made network that can implement some functions based on the mans comprehensive understanding for cerebral neural network (HAN, WANG, 1997). ANN is a mathematical model of simplified human brain neural network and is used to simulate the structures and functions of human brain neural network. ANN is a complex netw…