基于PSR-WSVM模型的边坡位移预测

为建立高精度的边坡位移预测模型，采用相空间重构（PSR）将边坡位移时间序列数据转换为多维数据，同时构造小波核函数改进的支持向量机模型，建立PSR-WSVM模型并应用于边坡位移预测。将PSR-WSVM模型预测结果与传统支持向量机（SVM）模型、小波支持向量机（WSVM）模型和基于相空间重构的支持向量机（PSR-SVM）模型预测结果进行对比，通过平均绝对误差（MAE）、平均绝对误差百分比（MAPE）和均方根误差（RMSE）3个精度评价指标验证PSR-WSVM模型的可行性。工程实例结果表明，PSR-WSVM模型预测结果的3个精度评价指标都优于另外3种模型，边坡位移预测的精度明显提升。     

RECENT TECTONIC DEFORMATION ANOMALY AND EARTHQUAKES IN GANSU-NINGXIA-QINGHAI AREA

1　IntroductionAccordingtogeologicalstructure ,theGansu Ningxia Qinghaiareabelongstothenortheastmar ginofQinghai Tibetblock .Thisareahasbeenpaidmuchattentionby geo specialistsinChinaandabroadbecauseofitssignificanttectonicmovement,itsintensiveseismicity ,anditsimportanceinearth quakehazardmitigation .IntheDevelopmentPro gramonNationalKeyBasicResearchesundertheProject“MechanismandPredictionofContinentalStrongEarthquakes”,themechanismsofcontinen talstrongearthquakesarestudied ,usinghypo…     

一种从经纬度网格资料获得正方形网格资料的插值方案

本文提出了一种把经纬度网格点上的气象要素值转化到正方形网格点上的多项式插值方案。对插值方案作了稳定性讨论和定量及定性分析。结果表明,这种插值方案方便可行,而且有广泛适用性。     

昆仑山口大地震与地形变异常的讨论

针对昆仑山口大地震，总结了多种地形变（大地测量）手段所显示的异常变化及其时空分布，结果显示：8．1级大震前存在空间尺度大，时间尺度的地形变前兆异常，简要介绍了相关的异常图像，给出了初步解释，并对未来震情的发展进行了探讨，认为近期内强震活动向华北迁移的可能性不大。     

形变大地测量学的进展、问题与地震预报

简要概括了形变大地测量学的革命性进展，研讨了它的科学特色、功能和定义以及对地球科学和防灾减灾的推动。形变大地测量学有助于从根本上击破多年来制约地震预报的“瓶颈”，但也存在不少急待解决的问题。着重研讨了在21世纪前10年，形变大地测量学如何依托多年的学科积累并充分受益于人造卫星和数字化等新技术，开展创新性研究和试验以推进地震预报。为此，对当前的研究工作提出了12条科学技术途径。最后对学科名称提出了建议。     

Prediction of Stellar Atmospheric Parameters using Instance-Based Machine Learning and Genetic Algorithms

In this article we present a method for the automated prediction of stellar atmospheric parameters from spectral indices. This method uses a genetic algorithm (GA) for the selection of relevant spectral indices and prototypical stars and predicts their properties, using the k-nearest neighbors method (KNN). We have applied the method to predict the effective temperature, surface gravity, metallicity, luminosity class and spectral class of stars from spectral indices. Our experimental results show that the feature selection performed by the genetic algorithm reduces the running time of KNN up to 92%, and the predictive accuracy error up to 35%. This revised version was published online in July 2006 with corrections to the Cover Date.     

成都市冬季重污染日气象条件成因分析及预报

本文通过对成都10个重污染日进行天气学分析,将污染浓度与气象要素进行聚类、研究了重污染日形成原因及污染浓度与气象要素的关系。在此基础上,建立了SO_2、TSP日平均浓度分级预报方程。     

Discriminating between pore‐filling load and bed‐structure load: a new porosity‐based method,exemplified for the river Rhine

Sediments contained in the river bed do not necessarily contribute to morphological change. The finest part of the sediment mixture often fills the pores between the larger grains and can be removed without causing a drop in bed level. The discrimination between pore‐filling load and bed‐structure load, therefore, is of practical importance for morphological predictions. In this study, a new method is proposed to estimate the cut‐off grain size that forms the boundary between pore‐filling load and bed‐structure load. The method evaluates the pore structure of the river bed geometrically. Only detailed grain‐size distributions of the river bed are required as input to the method. A preliminary validation shows that the calculated porosity and cut‐off size values agree well with experimental data. Application of the new cut‐off size method to the river Rhine demonstrates that the estimated cut‐off size decreases in a downstream direction from about 2 to 0·05 mm, covariant with the downstream fining of bed sediments. Grain size fractions that are pore‐filling load in the upstream part of the river thus gradually become bed‐structure load in the downstream part. The estimated (mass) percentage of pore‐filling load in the river bed ranges from 0% in areas with a unimodal river bed, to about 22% in reaches with a bimodal sand‐gravel bed. The estimated bed porosity varies between 0·15 and 0·35, which is considerably less than the often‐used standard value of 0·40. The predicted cut‐off size between pore‐filling load and bed‐structure load (D_c,p) is fundamentally different from the cut‐off size between wash‐load and bed‐material load (D_c,w), irrespective of the method used to determine D_c,p or D_c,w. D_c,w values are in the order of 10^?1 mm and mainly dependent on the flow characteristics, whereas D_c,p values are generally much larger (about 10⁰ mm in gravel‐bed rivers) and dependent on the bed composition. Knowledge of D_c,w is important for the prediction of the total sediment transport in a river (including suspended fines that do not interact with the bed), whereas knowledge of D_c,p helps to improve morphological predictions, especially if spatial variations in D_c,p are taken into account. An alternative to using a spatially variable value of D_c,p in morphological models is to use a spatially variable bed porosity, which can also be predicted with the new method. In addition to the morphological benefits, the new method also has sedimentological applications. The possibility to determine quickly whether a sediment mixture is clast‐supported or matrix‐supported may help to better understand downstream fining trends, sediment entrainment thresholds and variations in hydraulic conductivity.     

An operational multiscale system for hazards prediction, mapping, and response

By definition, a crisis is a situation that requires assistance to be managed. Hence, response to a crisis involves the merging of local and non-local emergency response personnel. In this situation, it is critical that each participant: (1) know the roles and responsibilities of each of the other participants; (2) know the capabilities of each of the participants; and (3) have a common basis for action. For many types of natural disasters, this entails having a common operational picture of the unfolding events, including detailed information on the weather, both current and forecasted, that may impact on either the emergency itself or on response activities. The Consequences Assessment Tool Set (CATS) is a comprehensive package of hazard prediction models and casualty and damage assessment tools that provides a linkage between a modeled or observed effect and the attendant consequences for populations, infrastructure, and resources, and, hence, provides the common operational picture for emergency response. The Operational Multiscale Environment model with Grid Adaptivity (OMEGA) is an atmospheric simulation system that links the latest methods in computational fluid dynamics and high-resolution gridding technologies with numerical weather prediction to provide specific weather analysis and forecast capability that can be merged into the geographic information system framework of CATS. This paper documents the problem of emergency response as an end-to-end system and presents the integrated CATS–OMEGA system as a prototype of such a system that has been used successfully in a number of different situations.     

钱二块铀矿床采铀注液结垢趋势的理论分析与预测

用离子系数矩阵法对钱二块铀矿床地浸采铀试验注液中存在的独立离子反应进行了确定,由溶度积规则及反应平衡原理,借助Matlab编程,估算出了钱二块铀矿床地浸采铀试验注液可能会生成的沉淀物种类及数量,为防治结垢提供了一定的理论依据.