System identification for nonlinear maneuvering of large tankers using artificial neural network

This paper deals with the application of nonparametric system identification to a nonlinear maneuvering model for large tankers using artificial neural network method. The three coupled maneuvering equations in this model for large tankers contain linear and nonlinear terms and instead of attempting to determine the parameters (i.e. hydrodynamic derivatives) associated with nonlinear terms, all nonlinear terms are clubbed together to form one unknown time function per equation which are sought to be represented by the neural network coefficients. The time series used in training the network are obtained from simulated data of zigzag maneuvers and the proposed method has been applied to these data. The neural network scheme adopted in this work has one middle or hidden layer of neurons and it employs the Levenberg–Marquardt algorithm. Using the best choices for the number of hidden layer neurons, length of training data, convergence tolerance etc., the performance of the proposed neural network model has been investigated and conclusions drawn.     

Climatic regimes and the recruitment rate of anchoveta, Engraulis ringens, off Peru

The recruitment rate of Peruvian anchoveta, Engraulis ringens, was studied to test the hypothesis that long-term environmental variation (regime shifts) had a significant impact on density-dependent processes governing the anchovy recruitment during the period 1963–2004. On the basis of previous defined regimes and turning points for the Humboldt Current System, we identified two groups of years for increased recruitment of anchoveta (1963–1971 and 1986–2004), and one unfavorable period (1972–1985). A common intercept and significantly different slopes were found when the recruitment rate was plotted as a function of the spawning stock biomass during those groups of years, suggesting that density-dependent effects on recruitment were affected during different climate regimes. The favorable (unfavorable) regime was characterized by higher (lower) zooplankton volumes, and with a higher frequency of colder (warmer) waters. Dome-shaped relationships between recruitment rate, spawning stock biomass and SST, were detected with a Generalized Additive Model for the favorable regime. Thus, recruitment could be explained by non-linear effects of environmental variables. Ultimately, climatic regimes are affecting the density-dependent effects on recruitment of anchoveta and the mechanisms involved may be associated with changes in the carrying capacity of the spawning habitat of anchoveta off Peru, which in turn are related with the effects of cold and warm regimes.     

RTK-GPS�����������񶯵Ķ�Ƶ�ʳɷַ���

???????RTK-GPS(????????λ??)???????????????????????????????????????????????????????RTK-GPS???????????????????????????????????????????????????????????е??     

DGPS测深技术在海底管道工程中的应用

简要介绍了差分全球定位系统(DGPS)的基本定位原理、DGPS测深技术中水深测量系统的硬件组成。重点分析了福建LNG站线湄洲湾海底管道工程成功采用DGPS测深技术进行勘测作业,使测量精度和工程效率得到极大地提高。这一工程实践经验说明,DGPS测深技术逐步为海底管道工程所采用,但其是一个不断探索、不断完善的过程,对今后我国沿海地区的海底管道工程的勘测建设具有一定的借鉴作用。     

热带太平洋深海微生物的若干生理生态特征

从2001年春、秋季于热带太平洋区采集到的深海样品中共分离到110株微生物,从中挑取31株进行形态特征和对环境理化因子适应特征的研究,同时利用Biolog微生物自动鉴定系统进行菌种鉴定和碳源代谢分析.结果表明:31株微生物中2株为酵母,21株为革兰氏阳性细菌,8株为革兰氏阴性细菌,来自底质的细菌菌株阳性菌占优势,而海水、蓝藻中阴性菌居多;温度、盐度、pH适应性试验表明,严格意义上的狭适性微生物不到总数的1/3,而具有较宽生态幅的广适性微生物占有相当大的比例.另一方面,耐冷菌、中度嗜盐菌和抗碱菌在这些微生物中的比例很高,同时,来自蓝藻的菌株大多数在4℃下不生长,而来自上覆水和底质的菌株可在4℃生长,这些都体现了微生物对生存环境的响应.31株微生物经Biolog鉴定12株得出鉴定结果.15株革兰氏阳性细菌对95种碳源的利用能力分析表明,不同菌株可利用碳源的数目从3种到46种不等,差异很大,体现了深海微生物营养类型的极大多样性;同时,发现有8种碳源可被一半以上的受试菌株所利用,这些碳源均是微生物各类代谢途径中的重要中间代谢物.     

基于国家海洋治理和全球气候变化的我国海洋灾害防治

为建立和完善现代化的海洋灾害防治体系,提高我国海洋治理和应对全球气候变化的能力,文章以全球治理和国家治理为背景,在明确致灾因子、承灾体、灾害以及灾害风险和管理等基本概念及其内涵的基础上,分析全球气候变化背景下我国海洋灾害及其风险的特征以及海洋灾害防治的关键性和基础性科学问题,并提出我国构建海洋灾害防治体系的建议。研究结果表明:在全球气候变化的影响下,我国沿海地区的海洋灾害风险复杂多变且有所提升;提出以群-环-域为主体的体系架构,研究全球气候变化与区域海洋的响应和反馈、全球气候变化背景下海洋灾害与风险的特征和规律以及综合海洋灾害风险评估和海洋灾害防治等问题;在我国构建海洋灾害防治体系的过程中,应加强科学研究以及技术和信息支撑、促进区域和全球联动联防以及提高全社会对海洋灾害的认知和防范水平。     

关于虚拟地理环境研究的几点思考

该文主要回答了目前被频繁问及的有关虚拟地理环境的几个问题。重点阐述了虚拟地理环境的概念、发展现状及其基本理论、方法、关键技术与应用,以及与传统地理信息系统的区别。指出虚拟地理环境是在空间数据库和地理模型管理基础上构建的、同时表达地理静态和模拟动态现象的、面向多用户的分布式协同虚拟环境。因此,虚拟地理环境突破地理信息系统以数据共享为核心的框架,走向以数据库和模型库为双核心的知识共享平台,进而形成一个新知识的生成环境。     

汀溪水库三维防洪调度管理信息系统研发

水库防洪调度是一个非常复杂的过程。水库防洪调度的信息化主要是借助测量、遥测、遥感(RS)、地理信息系统(G IS)、全球定位系统(GPS)等手段采集基础数据,构建数字化水库防洪数据管理平台和水库虚拟三维环境。在该平台和环境中,以系统软件和数学模型对水库流域的水雨情及洪水的调度方案进行模拟、分析和研究,提供决策支持,从而增强防洪调度决策的科学性和预见性。实践表明,通过RS、GIS技术建立的水库三维防洪调度系统能够为水库管理者提供水库防洪调度方案制定与分析、防洪调度决策等方面的强有力的、科学的辅助支持。本文结合厦门"汀溪水库三维防洪调度系统"的实际研发,探讨了RS和GIS技术在水库防洪调度中的应用。     

大流域3维水情信息系统的设计与实现研究

阐述了天津海河流域3维可视化应用系统的建设背景,系统设计及使用的关键技术。海河流域3维可视化应用系统（HH-VRGIS）是海河流域水利信息化的重要组成部分,它充分运用了现代GIS技术,先进的3维虚拟仿真可视化技术,大型数据库管理技术以及通信技术对水文专题信息的空间分析模型与查询技术进行了全面的整合,对海河流域的信息化管理,水资源的科学化调度和汛情及时准确的模拟和仿真做了基础研究。实践表明,该系统设计先进,界面友好,功能完善,运行稳定,具有较好的应用前景。     

A Nonlinear Representation of Model Uncertainty in a Convective-Scale Ensemble Prediction System

How to accurately address model uncertainties with consideration of the rapid nonlinear error growth characteristics in a convection-allowing system is a crucial issue for performing convection-scale ensemble forecasts. In this study, a new nonlinear model perturbation technique for convective-scale ensemble forecasts is developed to consider a nonlinear representation of model errors in the Global and Regional Assimilation and Prediction Enhanced System(GRAPES)Convection-Allowing Ensemble Predi...