A critical state model for sands dependent on stress and density

An elastoplastic model for sands is presented in this paper, which can describe stress–strain behaviour dependent on mean effective stress level and void ratio. The main features of the proposed model are: (a) a new state parameter, which is dependent on the initial void ratio and initial mean stress, is proposed and applied to the yield function in order to predict the plastic deformation for very loose sands; and (b) another new state parameter, which is used to determine the peak strength and describe the critical state behaviour of sands during shearing, is proposed in order to predict simply negative/positive dilatancy and the hardening/softening behaviour of medium or dense sands. In addition, the proposed model can also predict the stress–strain behaviour of sands under three-dimensional stress conditions by using a transformed stress tensor instead of ordinary stress tensor. Copyright © 2004 John Wiley & Sons, Ltd.     

A neural network approach to ship track-keeping control

This paper presents an on-line trained neural net work controller for ship track-keeping problems. Following a brief review of the ship track-keeping control development since the 1980's, an analysis of various existing backpropagation-based neural controllers is provided. We then propose a single-input multioutput (SIMO) neural control strategy for situations where the exact mathematical dynamics of the ship are not available. The aim of this study is to build an autonomous neural controller which uses rudder to regulate both the tracking error and heading error. During the whole control process, the proposed SIMO neural controller adapts itself on-line from a direct evaluation of the control accuracy, and hence the need for a “teacher” or an off-line training process can be removed. With a relatively modest amount of quantitative knowledge of the ship behavior, the design philosophy enables real time control of a nonlinear ship model under random wind disturbances and measurement noise. Three different track-keeping tasks have been simulated to demonstrate the effectiveness of the training method and the robust performance of the proposed neural control strategy     

COORDINATING DEVELOPMENT OF AGRICULTURAL RESOURCES AND ENVIRONMENT OF THE TROPIC REGION IN YUNNAN PROVINCE

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Studies on the distribution and antibacterial properties of Streptomyces in the intertidal zone of Southern Fujian

The oceans have rich resources of microbes. In recent years, searching for antibiotic of new structure and special biological activity from marine microbes has received great attention. This paper reports the results of the studies on the distribution and the antibacterial properties of Streptomyces in the intertidal zone of Southern Fujian. These studies have important significance to further investigate     

厦门筼筜港的形成与演变

本文根据实际调查的资料,概述了筼筜港区的地质地貌特征,重点论述了第四纪沉积物的成因和时代,阐述了该区的形成与演变过程,把它划分为5个发育阶段。     

基于神经网络的平底结构砰击压力预报

对利用神经网络预报平底结构入水砰击压力的方法进行了探讨。首先利用仿真软件计算各种情况下平底结构入水所产生的砰击压力，以此形成训练神经网络的数据集。其次利用数据集对三层反馈式网络进行了训练，讨论了不同隐含层节点数对该非线性系统的拟合能力，并且对梯度下降法、动量修正法和基于优化的LM算法的有效性和精度进行了比较，最后得出了适合平底结构入水砰击系统的网络结构。     

南海西沙西南海域表层沉积物特征

西沙西南海域表层沉积物样品矿物成分，地球化学，微体古生物分析测试结果表明：沉积物可分为７种类型，沉积环境主要是陆坡，部分为深海平原，海洋生物，海洋化学以及火山物质的沉积起到了积极的作用，陆源物质的影响较小，它们主要来源于北部大陆和南部岛礁等物源区。     

基于GIS的区域经济统计分析系统的设计与实现

随着经济的发展,区域间经济相互作用和影响的关系越来越密切,忽略空间相互作用的传统区域经济分析手段和方法开始显现出一些明显的不足。而GIS在处理和分析区域地理数据上具有强大的空间分析能力,为此我们引入GIS工具对区域经济进行分析,相较于传统的分析手法有了很大改善。本文以江西省区域经济数据为例,设计了一个基于GIS的区域经济统计分析系统,并利用Arcob-jects二次开发控件结合VB可视化编程语言,实现了大部分区域经济统计分析功能,最后并将结果进行网络发布。研究结果表明将GIS引入到区域经济统计分析中,更能正确、有效的揭示区域经济发展在空间上的联系,为区域经济研究决策提供服务。     

地震瞬时属性分析技术在岩溶勘查中的应用

介绍地震瞬时属性分析技术的原理及处理方法,分别对岩溶在地震剖面、瞬时振幅剖面、瞬时频率剖面、瞬时相位剖面上的表现特征作了说明.并结合实际资料进行多参数解释,进而确定地下岩溶的发育情况、分布范围和规模,同时对异常进行钻井验证,结果表明,地震瞬时属性分析技术比常规地震处理方法能更好地排除干扰,确定岩溶异常.