Collaborative Management of Natural Resources in San Diego Bay

This article presents the results of a three-year effort at applying information technology to the problem of collaborative natural resource management in San Diego Bay. As such, it represents an approach to integrated coastal zone management (ICZM). This effort resulted from a collaboration between the San Diego Supercomputer Center at the University of California, San Diego and the San Diego Bay Interagency Water Quality Panel for the purpose of (1) developing an environmental data repository to facilitate the acquisition and sharing of data and (2) the development of a visual model of the bay in support of the development of a comprehensive, coordinated management plan for San Diego Bay. It was determined from this study that information technology is an important and key component to ICZM but that sociopolitical factors may override the benefits of decision-support systems and should be considered at the outset of any project of this kind.     

灰色建模中数据缺失值处理方法探讨

为解决在利用灰色理论建模中,出现的数据缺失问题,本文提出综合利用SPSS软件的缺失值处理模块和稳健估计模块,针对数据的缺失机制进行处理的方法。使用该方法对缺失数据进行处理,以保证模型能够正常进行数据拟合。本文还利用了SPSS软件对某一实例中的缺失值进行了估计,并对缺失值填充后的结果进行了评价。     

小波分析在GPS动态监测数据粗差探测中的应用

文章分析了GPS监测数据序列中粗差的不确定性,提出了采用小波分析检测成片粗差,并通过实例进行应用分析,在此基础上进而对原变形数据序列中包含大量粗差的情况进行探测。实例分析表明,合理选择小波函数进行分析可以准确探测出粗差所在位置．解决了传统方法每次只能探测单个粗差的不足。     

来马路隧道超前地质预报典型不良地质体雷达数据解析

文章根据广西来宾至马山高速公路隧道超前地质预报成果,介绍了地质雷达数据采集、处理的要点,并结合探测实例分析了项目区常见的不良地质体(溶洞、断层带、裂隙密集带)的雷达反射波特征。     

基于PCA/ICA的中心区转向试验数据提取

基于主成分分析(Principal Component Analysis,PCA)及独立分量分析(Independent Component Analysis,ICA)方法,利用PCA降维功能及ICA独立盲源信号分离挖掘技术,对PCA/ICA计算方法进行改进,并应用于车辆中心区转向试验数据处理环节,有效排除了测试中各种干扰因素,实现了原始信号降噪,从统计学意义上保证了所提取数据指标的一致性。     

A hybrid Bayesian Network approach to detect driver cognitive distraction

Driver cognitive distraction (e.g., hand-free cell phone conversation) can lead to unapparent, but detrimental, impairment to driving safety. Detecting cognitive distraction represents an important function for driver distraction mitigation systems. We developed a layered algorithm that integrated two data mining methods—Dynamic Bayesian Network (DBN) and supervised clustering—to detect cognitive distraction using eye movement and driving performance measures. In this study, the algorithm was trained and tested with the data collected in a simulator-based study, where drivers drove either with or without an auditory secondary task. We calculated 19 distraction indicators and defined cognitive distraction using the experimental condition (i.e., “distraction” as in the drives with the secondary task, and “no distraction” as in the drives without the secondary task). We compared the layered algorithm with previously developed DBN and Support Vector Machine (SVM) algorithms. The results showed that the layered algorithm achieved comparable prediction performance as the two alternatives. Nonetheless, the layered algorithm shortened training and prediction time compared to the original DBN because supervised clustering improved computational efficiency by reducing the number of inputs for DBNs. Moreover, the supervised clustering of the layered algorithm revealed rich information on the relationship between driver cognitive state and performance. This study demonstrates that the layered algorithm can capitalize on the best attributes of component data mining methods and can identify human cognitive state efficiently. The study also shows the value in considering the supervised clustering method as an approach to feature reduction in data mining applications.     

TBM掘进数据标准化预处理方法研究北大核心CSCD

TBM信息化采集了海量数据,对TBM数据的标准化预处理是进行诸多研究的前提。基于此,提出了一种TBM掘进数据标准化处理方法,依托TBM现场施工掘进大数据,以破岩特征为依据选取基本掘进参数(刀盘转速、推进速度、刀盘推力及刀盘扭矩)分析掘进过程TBM数据特点,提出循环掘进过程空推段、上升段、稳定段及下降段起点的判别方法,对稳定段起点提出了标准差法判别方法、均值判别方法、直方图判别方法,满足实时和非实时的数据划分需求。最后对两个TBM工程的数据进行标准化预处理,实现施工大数据的标准化。结果表明,提出的标准化预处理方法可实现循环掘进过程数据的有效划分。研究成果可推广应用于众多TBM工程的数据标准化处理,有效实现机器学习数据库的建立。     

牵引试验车数据采集及处理系统设计与实现

牵引试验车数据采集及处理系统采集机车有关数据,并从RS232串口接收机车监控装置数据,同时,实时显示线路图和机车有关数据.介绍了该系统基于VC++6.0的实现方法,并着重讲述了系统的数据采集和串口数据接收过程.     

海量数据录入的几种技术方案的比较分析

基于B/S结构的0A系统,受浏览器的限制,在进行数据录入和数据校验时,如何保证用户使用的方便性、实时性以及安全性是企业Web OA系统开发实践中的难点问题.对此提出了5种技术解决方案,每个方案都按照方案概述、体系流程描述、难点问题解决过程描述以及方案优缺点描述的顺序进行说明,并对5种方案从用户需求的角度做了比较.     

基于决策偏好的ETC系统评价指标体系及评价方法

为更好地反映不同决策者对电子收费系统（ETC）评价的偏好,从政府、运营者和付费者三个主要利益主体的角度对ETC系统的评价指标及评价方法进行了研究。根据评价指标体系筛选原则,确定了基于决策偏好的ETC系统评价指标体系;通过综合分析成本-效益法（CBA）和数据包络分析法（DEA）的各自特点,依据基于决策偏好所确定的评价指标,同时引入当前一些比较好的算法来优化CBA,DEA和AHP法,建立数学模型,从而确立了基于决策偏好的综合评价方法。该方法较为全面地对ETC系统社会经济影响进行评价,所建立的指标体系和方法能更直观、更可靠地反映出决策者的决策偏好。