遂宁市大英县席家沟地区大气扩散参数研究

本文介绍了用平衡气球探测法研究遂宁市大英县席家沟地区大气扩散参数及结果,并与国标推荐值进行了比较。     

1/f噪声源与其在半导体器件可靠性评估中的应用

1／f噪声,由于其能够反映器件的质量与可靠性参数,其研究受到重视。本文首先较为系统地介绍了1／f噪声源两种较为成熟的理论：迁移率涨落模型和载流子涨落模型,最后介绍了几个1／f噪声与半导体器件参数漂移相关的实例。     

NONLINEAR MODELING AND PREDICTION OF A RIVER FLOW SYSTEM1

ABSTRACT: Model estimation and prediction of a river flow system are investigated using nonlinear system identification techniques. We demonstrate how the dynamics of the system, rainfall, and river flow can be modeled using NARMAX (Nonlinear Autoregressive Moving Average with eXogenuous input) models. The parameters of the model are estimated using an orthogonal least squares algorithm with intelligent structure detection. The identification of the nonlinear model is described to represent the relationship between local rainfall and river flow at Enoree station (inputs) and river flow at Whitmire (output) for a river flow system in South Carolina.     

A NEW LOOK AT FLOOD RISK DETERMINATION1

ABSTRACT: The probability distributions of annual peak flows used in flood risk analysis quantify the risk that a design flood will be exceeded. But the parameters of these distributions are themselves to a degree uncertain and this uncertainty increases the risk that the flood protection provided will in fact prove to be inadequate. The increase in flood risk due to parameter uncertainty is small when a fairly long record of data is available and the annual flood peaks are serially independent, which is the standard assumption in flood frequency analysis. But standard tests for serial independence are insensitive to the type of grouping of high and low values in a time series, which is measured by the Hurst coefficient. This grouping increases the parameter uncertainty considerably. A study of 49 annual peak flow series for Canadian rivers shows that many have a high Hurst coefficient. The corresponding increase in flood risk due to parameter uncertainty is shown to be substantial even for rivers with a long record, and therefore should not be neglected. The paper presents a method of rationally combining parameter uncertainty due to serial correlation, and the stochastic variability of peak flows in a single risk assessment. In addition, a relatively simple time series model that is capable of reproducing the observed serial correlation of flood peaks is presented.     

正交化方法在水质模型参数确定中的应用

本文根据常微分方程参数反问题的数学理论,将正交化方法同有限差分法结合用于确定水质模型参数,并与正则化方法、最速下降法和共轭梯度法作了比较。其计算结果对比表明,正交化方法具有快速、简便、可靠的特点。更适合于水质模型参数的确定。     

GEOLOGIC INFERENCE FROM “FLOW NET” TRANSMISSIVITY DETERMINATION: THREE CASE STUDIES1

A graphical inverse method for determining the regional transmissivity distribution was applied to three field problems. The study areas were the Hanford Site, Washington; the Rocky Mountain Arsenal, Colorado; and the Nevada Test Site, Nevada. This method can aid in flow system conceptualization by revealing the location of bedrock controls for groundwater flow. It is a valuable tool for aiding the hydrogeologist in asking questions about the nature of trends in the pattern of transmissivity values. Quantitative estimates of regional transmissivities can be used as starting points for further parameter refinement. Sensitivity analysis using Monte Carlo simulation shows that quantitative estimates of transmissivity can be obtained when measurement error in the hydraulic head does not cause a large error in the hydraulic gradient.     

PARAMETRIC ESTIMATION OF COVARIANCES OF REGIONALIZED VARIABLES1

ABSTRACT: The usefulness of stochastic models in describing the spatial variability of hydrogeologic quantities, such as permeability, storativity, piezometric head, seepage velocity, and solute concentrations is now widely recognized. In practice, these quantities are represented as the sum of a well-structured component, or drift, and a more erratic fluctuation component which is described statistically through its covariance function. This paper reviews some of the most recent and most promising methods for the estimation of parameters of these covariances from existing data. They are maximum likelihood, restricted maximum likelihood, minimum-variance unbiased quadratic estimation, and minimum-norm (weighted least squares) estimation. The applicability of such methods to conditional and unconditional probability problems is discussed.     

四川盆地森林覆盖率自然影响因素分析

本文对四川盆地森林覆盖率的影响因素进行逐步回归分析,结果表明影响森林覆盖率的自然因素是综合的,它包括气候、地貌、土壤等自然条件。其中以7月降水量、地形崎岖度、山地比例、酸性紫色土比例及土地垦殖系数等作为决定四川森林覆盖率变化的最重要因素,这5个因素即可解释盆地森林覆盖率80%以上的变化。     

Short-term wind speed forecasting based on random forest model combining ensemble empirical mode decomposition and improved harmony search algorithm

ABSTRACT

Wind speed forecasting plays an important role in power grid dispatching management. This article proposes a short-term wind speed forecasting method based on random forest model combining ensemble empirical modal decomposition and improved harmony search algorithm. First, the initial wind speed data set is decomposed into several ensemble empirical mode functions by EEMD, then feature extraction of each sub-modal IMF is performed using fast Fourier transform to solve the cycle of each sub-modal IMF. Next, combining the high-performance parameter optimization ability of the improved harmony search algorithm, two optimal parameters of random forest model, number of decision trees, and number of split features are determined. Finally, the random forest model is used to forecast the processing results of each submodal IMF. The proposed model is applied to the simulation analysis of historical wind data of Chaoyang District, Liaoning Province from April 27, 2015 to May 22, 2015. To illustrate the suitability and superiority of the EEMD-RF-IHS model, three types of models are used for comparison: single models including ANN, SVM, RF; EMD combination models including EMD-ANN, EMD-SVM, EMD-RF; EEMD combination models including EEMD-ANN, EEMD-SVM, EEMD-RF. The analysis results of evaluation indicators show that the proposed model can effectively forecast short-term wind data with high stability and precision, providing a reference for forecasting application in other industry fields.     

基于驾驶适宜性检测的沙漠公路驾驶员视觉特性分析

利用动体视力检测仪,对沙漠公路行车途中汽车驾驶员进行包括静视力和动体视力在内的视觉特性的实地测试,并就获得的1004个有效样本的检测数据进行统计整理,对受测驾驶员静、动体视力总体情况及其与驾驶员年龄、驾龄、持续行车时间、检测时的气温等因素之间的关系进行分析研究。对驾驶员视觉特性的实测分析表明:沙漠公路受测驾驶员静视力和动体视力平均值分别为1.3和0.7;动体视力相对于静视力的平均下降幅度为44.75%,远高于绿洲地区。关联度分析也表明,驾驶员的年龄、驾龄、驾车时间以及测试温度4项因素对其静视力、动视力以及视力降幅均具有较强的相关性,关联度均在0.76以上。