基于MATLAB COM组件的变形监测与分析软件开发

论述了桥梁变形自动监测系统数据的频谱分析以及小波分析方法,并利用MATLAB编译的COM组件,实现了在VC中调用该COM组件以实现脱离MATLAB环境的变形分析软件开发。     

复杂地貌形态多比例尺表达的二维小波分析研究

针对复杂地貌形态的多比例尺表达中的等高线容易相交、地性特征描述困难和表达过程缺乏自适应等难题，提出了基于小波理论的复杂地貌形态的多比例尺表达模型，为上述问题的解决提供了新的思路和有效途径。     

Wavelet analysis and nonparametric test for climate change in Tarim River Basin of Xinjiang during 1959–2006

Using wavelet analysis, regression analysis and the Mann-Kendall test, this paper analyzed time-series (1959–2006) weather data from 23 meteorological stations in an attempt to characterize the climate change in the Tarim River Basin of Xinjiang Uygur Autonomous Region, China. Major findings are as follows: 1) In the 48-year study period, average annual temperature, annual precipitation and average annual relative humidity all presented nonlinear trends. 2) At the 16-year time scale, all three climate indices unanimously showed a rather flat before 1964 and a detectable pickup thereafter. At the 8-year time scale, an S-shaped nonlinear and uprising trend was revealed with slight fluctuations in the entire process for all three indices. Incidentally, they all showed similar pattern of a slight increase before 1980 and a noticeable up-swing afterwards. The 4-year time scale provided a highly fluctuating pattern of periodical oscillations and spiral increases. 3) Average annual relative humidity presented a negative correlation with average annual temperature and a positive correlation with annual precipitation at each time scale, which revealed a close dynamic relationship among them at the confidence level of 0.001. 4) The Mann-Kendall test at the 0.05 confidence level demonstrated that the climate warming trend, as represented by the rising average annual temperature, was remarkable, but the climate wetting trend, as indicated by the rising annual precipitation and average annual relative humidity, was not obvious.     

小波多尺度分析在煤田火烧区磁法探测中的应用

根据小波多尺度分析原理,分解磁异常。理论模型及实例分析表明,小波多尺度分析对分解后的磁异常,可按需要区分不同地质意义,突出目标地质体,抑制干扰,划分煤田的火烧区烧变岩边界。     

综合小波分析与分形方法进行弱磁异常识别

利用小波分析塔式算法对单一分形模型数据进行处理,结合"随机共振"理论,对高精度弱磁异常中的噪声和误差进行有效的分析评价,依据趋势分析方法获得的剩余磁异常,提出"加窗移动"最小二乘方法对应用非整数阶微积分的布郎运动正态随机行走进行控制,为高精度弱磁异常的有效识别提供有益的指导.     

常州雷暴的气候特点及多普勒雷达回波特征

利用常州基本观测站1952-2007年长序列的雷暴观测资料和多普勒雷达回波资料,采用数理统计和小波变换方法,对常州雷暴的变化规律、周期特征以及雷达回波特征进行了分析.结果表明:(1)雷暴日数年代际间差异显著.(2)雷暴年际变化很大,最大值为最小值的5.9倍;雷暴日数总体呈显著减少的趋势.(3)夏季为雷暴高发季节,占总雷暴日数的66.8%.(4)月际变化差异大,雷暴集中出现在4-9月,其中7、8月为雷暴高发月.(5)从日分布来看,傍晚出现次数最多,其次为下午,上午出现最少.(6)常州年雷暴日数分布主要表现为12a(年代际)震荡周期贯穿在整个56年里;1952-2004年存在着非常明显7a左右的次周期特征;1968-2007年还存在3～4a的小周期特征.(7)常州雷暴的雷达回波基本反射率因子一般在30～65dBz之间,回波顶高为6～17km.(9)常州雷暴雷达回波移向主要有五类:西南东北向、东南西北向、西北东南向、旋转、局地生成.另外对常州雷雨大风和冰雹进行了统计分析,发现:7月为雷雨大风最高发月;5月和7月为冰雹最高发月.     

Simulation of streamflow with statistically downscaled daily rainfall using a hybrid of wavelet and GAMLSS models

ABSTRACT

A rainfall–streamflow model is proposed, in which a downscaled rainfall series and its wavelet-based decomposed sub-series at optimum lags were used as covariates in GAMLSS (Generalized Additive Model in Location, Scale and Shape). GAMLSS is applied in climate change impact assessment using CMIP5 general climate model to simulate daily streamflow in three sub-catchments of the Onkaparinga catchment, South Australia. The Spearman correlation and Nash-Sutcliffe efficiency between the observed and median simulated streamflow values were high and comparable for both the calibration and validation periods for each sub-catchment. We show that the GAMLSS has the capability to capture non-stationarity in the rainfall–streamflow process. It was also observed that the use of wavelet-based decomposed rainfall sub-series with optimum lags as covariates in the GAMLSS model captures the underlying physics of the rainfall–streamflow process. The development and application of an empirical rainfall–streamflow model that can be used to assess the impact of catchment-scale climate change on streamflow is demonstrated.     

基于小波分解的西太平洋副热带高压模糊推理预测

基于NCEP/NCAR再分析资料,讨论了西太平洋副高脊线与其前期位置的相互关系,并在此基础上用小波分解和自适应模糊推理方法,对副高脊线进行集成建模和预测.基于小波分解重构的副高脊线短期活动集成预测结果表明,该方法可有效降低预报难度,明显改进和提高了副高脊线短期活动的预报准确率.     

模拟退火粒子群与小波的地基沉降预测应用

针对粒子群优化算法易陷入局部极小值问题,改进学习因子使其自适应调整,并与具有良好全局搜索能力的模拟退火算法结合,充分利用两种算法各自的优点,同时结合小波分析去噪,优化神经网络参数,对地基累计沉降数据进行预测,并与标准粒子群优化算法做了对比,实验表明两种方法的结合具有良好的全局和局部搜索能力,预测精度高。     

气候多层次的趋势预报

论述了子波气候诊断中的边界效应和非周期性对趋势预报的影响，在消除子波变换边界效应基础上，将气候层次理论和子波诊断技术相结合，提出了气候多层趋势预报法则和评判标准，最后利用若干气候资料进行了多层次趋势预报，试验表明，相似延伸法能有效地消除边界效应，提出了气候多层次趋势预报法是可行的。