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。     

Analysis of mapping coverage obtained from spacecraft

An exact analysis of the coverage obtained by spacecraft using cross-track scanning and nadir-centered conical imaging, under imposed viewing obliqueness and resolution requirements, is presented. In addition to exact expressions for the area acquired and the area acquisition rate, envelope theory is introduced to obtain the boundary of the imaged area. These expressions are relatively compact, allowing rapid machine computation. The effects of the sun phase angle, and of imaging system limitations are also examined. The Galileo mission encounter with Callisto is used as a numerical example, from which certain general conclusions are drawn regarding optimal imaging trajectories.     

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.     

Transforming observational data and theoretical isochrones into the ACS/WFC Vega-mag system

We propose a zero-point photometric calibration of the data from the Advanced Camera for Surveys (ACS) Wide Field Channel (WFC) on board the Hubble Space Telescope , based on a spectrum of Vega and the most up-to-date in-flight transmission curves of the camera. This calibration is accurate at the level of a few hundredths of a magnitude. The main purpose of this effort is to transform the entire set of evolutionary models into a simple observational photometric system for ACS/WFC data, and to make them available to the astronomical community. We provide the zero-points for the most used ACS/WFC bands, and give basic recipes for calibrating both the observed data and the models. We also present the colour–magnitude diagram from ACS data of five Galactic globular clusters, spanning the metallicity range  −2.2 <[Fe/H] < −0.04  , and we provide fiducial points representing their sequences from several magnitudes below the turn-off to the red giant branch tip. The observed sequences are compared with the models in the newly defined photometric system.     

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。