基于EEMD-RVM的陀螺漂移混合建模预测

陀螺漂移序列具有非平稳和非线性的特点,针对单一模型难以对其实现精确预测的问题,提出一种基于集合经验模态分解(EEMD)和相关向量机(RVM)的混合建模方法,实现对陀螺漂移序列的区间预测.首先,利用集合经验模态分解将漂移序列分解为多个模态和一个余量;将模态区分为噪声和趋势两个分量,对噪声分量建立分布模型,对趋势分量建立RVM模型,两者等权相加还原得混合模型;最后,给定置信度,得到置信区间预测结果.将该方法用于某振动陀螺漂移序列预测实例,结果表明:该混合预测模型能准确预测陀螺漂移,其中RVM的预测精度达到99.86%,且验证集以给定的置信度落在预测区间内,可为陀螺的寿命预测和性能分析提供依据.     

A method for the correction of drift in movement analysis

A method is proposed for the correction of drift over cyclic three-dimensional kinematic data during treadmill locomotion. An adaptive least-squares drift correction algorithm (ALSDC) is developed from the operational definition of no drift. This method includes automatic selection of least-squares polynomial degree and sequential processing of large data sets.     

基于ER的陀螺漂移组合预测模型

针对目前单一预测模型预测精度不高,使用范围受限的不足,利用D-S证据理论在数据融合中的优点,把证据推理(ER)与支持向量回归机预测理论有机结合建立了组合预测模型,提出了基于ER的组合预测算法,并以陀螺仪为例,实现了漂移预测.结果表明,该模型与算法是可行且有效的.     

A surface ocean trajectories visualization tool and its initial application to the Galician coast

Alavai is a free tool built with Processing to visualize forecasts of drift trajectories in the sea in a very fast and user-friendly graphic environment. It plots trajectories of both passive particles trapped near the ocean surface and oil slicks. Input data come from an operational configuration of the ROMS ocean model focused on the Euroregion Galicia (Spain) – North Portugal, however, this tool is easily adaptable to run with outputs coming from any operational high resolution ocean model configuration. The Prestige accident is used here in hindcast mode to demonstrate the main characteristics of Alavai.     

European operational air quality forecasting system by using MM5–CMAQ–EMIMO tool

Three Dimensional air quality modelling systems have experienced a considerable advance during the last decade. Sophisticated numerical methods have been developed also to gather most of the computer capabilities which have also experimented important advances. Parallel computing is also an option which is considered more and more important nowadays due to the relative slow process on single computer processors during last years. In this contribution we have implemented an air quality real-time operational forecasting system which covers all Europe by using the MM5–CMAQ–EMIMO air quality modelling system. This system is a step forward from the already developed system which covered the Iberian Peninsula in 2002. The CMAQ 4.5 version (September, 2005) has been incorporated to the application. MM5 and CMAQ models are, respectively the meteorological mesoscale and the dispersion drivers. The EMIMO model has been progressively updated by using the new Corine Land Cover for Europe (EEA) with 100 m spatial resolution. We have developed a GIS oriented internet interface which allows the user to access immediately to pollution time series and hourly maps for the next 48–72 h forecast for criteria pollutants (those limited by the corresponding EU Directives). The visual information is adapted to the specific legislation for each pollutant so that the information is related to the possible exceedances of the different concentrations averaged over different periods of time. The system is expected to be used as an operation tool to provide boundary and initial conditions for actual and future national, regional and city air quality forecasting systems.     

基于少参数二阶Volterra级数的陀螺漂移预测

针对陀螺漂移角速度的非线性时间序列预测问题,提出了一种基于少参数二阶(RPSO)Volterra级数的仿射投影(AP)自适应辨识算法,建立了基于RPSO Volterra级数的非线性预测模型。根据预测模型中两个参数向量位置可互换的特性,AP算法推导出两个结构相似的迭代公式。然后给出基于遗传算法优化AP算法步长参数及建模的完整步骤。最后通过实测的陀螺漂移数据验证所提出的算法,在极短的时间内建立出模型并获得了精确的预测结果。     

Ocean surface Stokes drift from scatterometer observations

Stokes drift, a mean Lagrangian motion induced by ocean surface gravity waves, plays an important role in modifying the upper ocean circulation. In this study, two empirical models are developed to estimate ocean surface Stokes drift U_ss, based on a multilayer-perceptron Back-Propagation Neural Network (BP NN) algorithm, using buoy data collocated with European Remote Sensing (ERS) data, and using (1) bulk wave parameters and (2) spectral wave density. Both BP NN models perform reasonably well, with correlation coefficients of 0.92 between the retrieved U_ss and buoy measurements, for the former bulk-parameter-based NN model, compared to 0.87, for the latter spectral wave-density-based NN model. U_ss values were estimated over the global ocean during 27–29 August 1998. We found U_ss in the range from 2 to 36 cm s^?1 with an average of 9 cm s^?1, which is in good agreement with previous observations. With the retrieved U_ss, we calculated the Langmuir number L_at and the scaled Langmuir vertical turbulent velocity. The distribution of L_at (generally in the range 0.25–0.58) provides a measure of the dominance of Langmuir turbulence over kinetic energy turbulence in regions with high U_ss, such as the westerlies in the Southern Ocean.     

Expected impact of the future SMOS and Aquarius Ocean surface salinity missions in the Mercator Ocean operational systems: New perspectives to monitor ocean circulation

Sea Surface Salinity (SSS) has never been observed from space. The SSS from planned satellite missions such as Soil Moisture and Ocean Salinity (SMOS) and Aquarius is a key to better understanding how ocean circulation is related to water cycle and how both these systems are changing through time.The Observing System Simulation Experiments (OSSEs) presented in this paper has been carried out with an ocean forecasting system developed within the French oceanographic Mercator Ocean context. They consist in hindcast experiments assimilating an operational dataset (Sea Surface Temperature (SST), in-situ profiles of temperature and salinity and Sea Level Anomalies (SLA)) and various simulated SMOS and Aquarius Sea Surface Salinity (SSS) data. These experiments use an eddy permitting model (1/3°) covering the North Atlantic from 20°S to 70°N. The new generation of fully multivariate assimilation system referred to as SAM2v1 which is being developed from the SEEK (Singular Evolutive Extended Kalman) algorithm is used. This scheme is a Reduced Order Kalman Filter using a 3D multivariate modal decomposition of the forecast error covariance.The OSSEs enabled us to show the positive impact of SSS assimilation on the Mercator Ocean operational forecasting system. These experiments particularly show the importance to specify appropriated observation errors and the impact of having and/or combining different observing system. Several conclusions can be highlighted such as the importance of the space/time scales consistency between the data products and our ocean prediction systems. This study has to be considered as an important step for assimilation of SSS measured from space. Further studies have to be conducted with other simulated data, other oceanic configurations and other improved assimilation schemes.     

A probabilistic model for predicting software development effort

Recently, Bayesian probabilistic models have been used for predicting software development effort. One of the reasons for the interest in the use of Bayesian probabilistic models, when compared to traditional point forecast estimation models, is that Bayesian models provide tools for risk estimation and allow decision-makers to combine historical data with subjective expert estimates. In this paper, we use a Bayesian network model and illustrate how a belief updating procedure can be used to incorporate decision-making risks. We develop a causal model from the literature and, using a data set of 33 real-world software projects, we illustrate how decision-making risks can be incorporated in the Bayesian networks. We compare the predictive performance of the Bayesian model with popular nonparametric neural-network and regression tree forecasting models and show that the Bayesian model is a competitive model for forecasting software development effort.     

星载微波辐射计AMSR-E在台风分析中的应用

基于洋面上的微波辐射传输模型,采用多元线性回归算法,建立了海洋-大气参数的反演算式,并对其进行了验证。在此基础上,根据AMSR-E的反演结果,结合微波图像,对2005年“麦莎”和“泰利”两次台风的发生发展过程进行了初步分析和比较。结果表明,反演算式的精度接近于美国雪冰数据中心公布的业务产品,反演结果比较符合实际情况,微波图像可以较好地反映台风发生发展过程中的变化特征。     

A GIS based component-oriented integrated system for estimation, visualization and analysis of road traffic air pollution

Road traffic is a dominant source of air pollution. Therefore it is necessary to provide decision-makers with up-to-date emission information in an easily understandable form. To achieve this goal we have integrated existing emission calculation software with a graphical user interface, which includes a GIS (geographical information system) component. The paper first gives a summary of the basic road traffic emission model and then focuses on the design and implementation of the computer application with the emphasis on the used component and GIS technology. The integrated emission evaluation system offers entirely new ways of using the emission model and gives additional visualization and analysis possibilities.     

基于Volterra 级数并行递推AP 算法的陀螺漂移预测

为了预测某导弹陀螺漂移趋势,以该陀螺漂移角速度时间序列为对象,建立基于Volterra级数的非线性时间预测模型,提出了一种基于Volterra级数的并行递推放射投影AP自适应算法.以系统Volterra核向量增量的模与某约束总和为损失函数,按照最陡下降原理导出各阶Volterra核更新公式;再利用矩阵求逆引理递推求取各阶Volterra子系统自相关逆矩阵导出算法.某导弹实测的陀螺漂移数据预测应用研究表明,该算法运算速度快、预测精度高.     

Simulation in public sector management: a case study

We detail the development and application of a simulation model to aid decision making concerning the procedures followed in the Office of Film and Literature Classification, by forecasting the effects of possible management initiatives. The major variables are — the number of censors, the volume of publications to be classified (with special emphasis on computer technology publications) and the procedures, in particular, the number of censors with decision-making powers. A model of the system was developed using Extend; a simulation software package designed to aid decision support. This model was used to investigate the utilization of "decision-makers", and to identify and locate the bottlenecks, in the system under a number of different scenarios suggested by the client. There is also the flexibility to include additional duties that might be imposed on the Office.     

惯性导航系统陀螺漂移补偿算法研究

分析了几种计算惯导系统导航陀螺漂移的方法，构思了一种组合导航系统模式，在水下即可完成对惯导的校正，对导航陀螺漂移进行补偿。同时还提出了对导航陀螺漂移补偿的优化组合算法。理论分析及计算机仿真结果均表明，应用该组合导航系统可大大提高潜艇的导航定位精度和隐蔽性。     

Cost Effective Smart System for Water Pollution Control with Underwater Wireless Sensor Networks: A Simulation Study

The underwater sensor network is a rapidly developing area of research with a wide range of applications such as data collection in the ocean, pollution monitoring, and ocean sampling. One of the most researched areas is the coverage of underwater sensor networks, which are the basis of many applications. The coverage is usually related to how effectively a network is monitored by the sensor. There are major problems in the ocean or marine region, especially in water pollution. Underwater pollution generally causes acidification, plastic residues, and toxins. Today, the determination of this pollution is carried out through a human surveillance monitoring process. Therefore, there is a need for an automatic and intelligent monitoring system to identify the formation of pollution. The proposed simulation model defines the intelligent sensor-based monitoring system that identifies and alarms the formation of underwater pollution. Aloha was chosen as the medium access protocol for the cost-effective system in which we designed the simulation model. The efficiency of the system has been shown to be more stable, cost-effective and manageable than the monitoring process involving the existing human surveillance by testing with the simulation model.     

支持向量机应用于大气污染物时间序列预测

阐述了支持向量机应用于大气污染物时间序列预测的具体方法,建立了大气污染物时间序列的支持向量机预测模型.该方法将支持向量杌应用于大气污染物浓度预测:首先通过选择合适的信息量准则来确定模型阶数:而后通过实验的方法选择参数从而形成支持向量机的训练样本集,在此基础上建立了基于支持向量机的时间序列大气污染预测模型.实例表明,无论是在仿真过程还是在预测过程,支持向量机都具有很高的预测精度.因此.采用支持向量机方法对大气污染物时间序列进行预测分析是可行的.     

基于共享矢量链的多任务概念漂移分类方法

增强型时间自适应支持向量机在针对单一概念漂移问题时展现出了良好效果,但是无法协同求解多个概念漂移问题.然而,在很多应用场景中,有时会包含数个具有内在相关性的非静态数据集,它们各自的分类模型应充分考虑这种关联.为了反映出各概念漂移分类模型之间的相关部分,提出共享矢量链的概念,并开发面向多任务概念漂移问题的共享矢量链支持向量机(SVC-SVM).在模拟数据集及气体传感器阵列漂移数据集上的实验结果显示,协同求解多个具有相关性的概念漂移问题能够有效提升各自的泛化能力.     

基于混沌分析的导弹惯性器件非线性故障预报

通过一定方法对陀螺仪的性能进行预测,是提高惯性器件的精度及保证整个控制系统可靠性的有效方法之一,论文在分析基于混沌分析的非线性预测方法的基础上,将陀螺仪误差系数随时间的漂移看作一个混沌过程,利用陀螺仪漂移测试数据进行相空间重构,在重构的相空间上,用基于最大Lyapunov指数的混沌预测方法对陀螺仪漂移进行预测,提出了一种新的基于混沌分析的陀螺仪漂移性能预报方法;通过基于MATLAB仿真实验证明,与经典的基于马尔可夫的预测方法相比该方法有更好的预测效果.     

A case study in rapid prototyping

A case study in rapid prototyping of a new language processor is described. A quick version of the system was developed in SNOBOL4, revised in SNOBOL4, and then rewritten in Pascal. This led to an operational system very early in the development cycle where operational characteristics of the system could be tested easily. The goals of this experiment as well as some of the results are described.     

Assessing architectural drift in commercial software development: a case study

Objectives: Software architecture is perceived as one of the most important artefacts created during a system's design. However, implementations often diverge from their intended architectures: a phenomenon called architectural drift. The objective of this research is to assess the occurrence of architectural drift in the context of de novo software development, to characterize it, and to evaluate whether its detection leads to inconsistency removal. Method: An in vivo, longitudinal case study was performed during the development of a commercial software system, where an approach based on Reflexion Modelling was employed to detect architectural drift. Observation and think‐aloud data, captured during the system's development, were assessed for the presence and types of architectural drift. When divergences were identified, the data were further analysed to see if identification led to the removal of these divergences. Results: The analysed system diverged from the intended architecture, during the initial implementation of the system. Surprisingly however, this work showed that Reflexion Modelling served to conceal some of the inconsistencies, a finding that directly contradicts the high regard that this technique enjoys as an architectural evaluation tool. Finally, the analysis illustrated that detection of inconsistencies was insufficient to prompt their removal, in the small, informal team context studied. Conclusions: Although the utility of the approach for detecting inconsistencies was demonstrated in most cases, it also served to hide several inconsistencies and did not act as a trigger for their removal. Hence additional efforts must be taken to lessen architectural drift and several improvements in this regard are suggested. Copyright © 2010 John Wiley & Sons, Ltd.