线性回归法在地下水水质分析中的应用

运用逐步线性回归的理论方法,分析研究区的地下水水质指标间的相关性,研究区属砷元素富集地区,对研究区建立砷含量与其他指标之间的线性回归模型,确定砷含量与HPO4-2、Fe、I-,Br-的含量相关性较显著。此模型可以用于研究区的地下水环境的规划、评价、研究工作中。     

辽宁省典型地形测风塔缺测数据线性计算适用性分析

利用辽宁省典型地形26座测风塔和6个同期气象站的逐时风速实测数据,采用不同时间尺度（月、季、年）的线性拟合并结合风切变指数拟定7个方案重构测风塔缺测风速数据,并对各拟定重构方案进行误差检验。结果表明：辽宁省典型地形测风塔缺测数据重构主要以季节尺度的线性拟合及其结合风切变指数的两个方案（方案3和方案7）为最优方案,且上述两个方案的空间分布具有区域性特征,其中,辽宁北部的平原和丘陵、辽宁东南部的沿海平原和沿海丘陵主要以方案7为最优方案,辽宁西部的丘陵和山地主要以方案3为最优方案,个别地区以方案1或方案4为最优方案。温带大陆性季风气候区所具有的季节性风速变化和固有的地形地势特征及其对风切变指数的影响,是辽宁省典型地形测风塔缺测数据重构最优方案空间分布呈区域性特征的主要成因。     

线性空间与非线性函数空间测量平差效果比较

用顾及一阶泰勒项的线性平差方程，顾及地阶泰靶项的线性平差方法及非线性函数空间的平差方法对同一平差问题进行了研究，在比较其平差效果的基础上论述了建立非线性函数空间测量平差与数据处理理论的必要性。     

基于高阶累积量ARMA模型线性非线性结合的地震子波提取方法研究

在地震子波非因果、混合相位的假设下,本文应用自回归滑动平均(ARMA)模型对地震子波进行参数化建模,并提出利用线性(矩阵方程法)和非线性(ARMA拟合方法)相结合的参数估计方式对该模型进行参数估计.在利用矩阵方程法确定模型参数范围的基础上,利用累积量拟合法精确估计参数.理论分析和仿真结果表明,该方式有较好的适应性：一方面提高了子波估计精度,避免单独使用矩阵方程法在短数据地震记录情况下可能带来的估计误差;另一方面提高了子波提取运算效率,降低了ARMA模型拟合方法参数范围确定的复杂性,避免了单纯使用滑动平均（MA）模型拟合法估计过多参数所导致的运算规模过大问题.初步应用结果表明该方法是有效可行的.     

"93.5"黑风暴的对称不稳定诊断分析

利用一次较好地模拟了“９３．５”黑风暴的ＭＭ４中尺度模式三个时次的输出资料,应用线性和非线性对称不稳定的判据对这次强沙尘暴天气过程进行诊断分析。结果表明,线性理论判据中的湿对称不稳定为这次过程的一种可能机制。非线性理论的分析结果表明,这次飑线过程不但与条件对称不稳定和尖点突变有关,且其移速较线性理论更符合实际过程。     

全球气候变暖背景下兰州地面平均气温的变化

利用兰州1932-2002年逐月地面月平均温度资料，分析了兰州71年来温度的基本气候特征、年代际变化、突变、异常冷暖和变化趋势等。分析表明：71年来年和四季气温大体都经历了两个暖期和一个冷期．第一暖期的增暖主要在春、夏、秋季。冬季则处在冷期中；第二暖期首先从冬季开始，四季间相隔1～2年后陆续大幅度增暖．第二暖期增暖幅度明显高于第一暖期，持续时间也长于第一暖期。最大的特点是四季同时增暖，冬季增暖幅度最大。1960年代是最冷的10年，以夏季降温最为明显；1990年代是最暖的10年，以冬季增暖最为明显。1990年代发生异常的频次最高，其次是1960年代和1970年代，最少的是1980年代。71年来．兰州年平均气温以1．4℃／100a线性趋势上升，高于北半球和全国水平，近10年冬秋季增温率最大。     

环境剪应力值τ0的稳定性和预测效能分析

利用峰值加速度αp、峰值速度νp和峰值位移dp,计算了广东省河源地区64个地震的环境剪应力值τ0。结果表明,同一地震的τ0α、τ0v、τ0d可相差很大,τ0v、τ0d的误差主要来自地震矩M0。因此,如果不能从震源谱计算M0,则以峰值加速度方法计算τ0误差最小。剪应力值为使用震级序列分析地震趋势提供了明确的物理基础。即高震级地震多发说明应力场处于高强度背景,有发生更大地震的可能;反之则为低应力场背景,发生更大地震的可能性不大。公式分析和实际数据拟合得到lg（τ0）与ML有很好的线性相关,因此震级序列与剪应力值序列的地震预测效能是基本相同的。但与震级序列相比,τ0的计算显然要复杂,且误差也较大。     

Estimation of the Friction Velocity in Stably Stratified Boundary-Layer Flows Over Hills

A method is suggested for the calculation of the friction velocity for stable turbulent boundary-layer flow over hills. The method is tested using a continuous upstream mean velocity profile compatible with the propagation of gravity waves, and is incorporated into the linear model of Hunt, Leibovich and Richards with the modification proposed by Hunt, Richards and Brighton to include the effects of stability, and the reformulated solution of Weng for the near-surface region. Those theoretical results are compared with results from simulations using a non-hydrostatic microscale-mesoscale two-dimensional numerical model, and with field observations for different values of stability. These comparisons show a considerable improvement in the behaviour of the theoretical model when the friction velocity is calculated using the method proposed here, leading to a consistent variation of the boundary-layer structure with stability, and better agreement with observational and numerical data.     

Radially accelerated optimal feedback orbits in central gravity field with linear drag

The solution of a feedback optimal control problem arising in orbital mechanics is addressed in this paper. The dynamics is that of a massless body moving in a central gravitational force field subject also to a drag and a radial modulated force. The drag is linearly proportional to the velocity and inversely proportional to the square of the distance from the center of attraction. The problem is tackled by exploiting the properties of a suitably devised linearizing map that transforms the nonlinear dynamics into an inhomogeneous linear system of differential equations supplemented by a quadratic objective function. The generating function method is then applied to this new system, and the solution is back transformed in the old variables. The proposed technique, in contrast to the classical optimal control problem, allows us to derive analytic closed-loop solutions without solving any two-point boundary value problem. Applications are discussed.     

Comparison between neuro-fuzzy and fractal models for permeability prediction

We have used different techniques for permeability prediction using porosity core data from one well at the Maracaibo Lake, Venezuela. One of these techniques is statistical and uses neuro-fuzzy concepts. Another has been developed by Pape et al. (Geophysics 64(5):1447–1460, 1999), based on fractal theory and the Kozeny–Carman equations. We have also calculated permeability values using the empirical model obtained in 1949 by Tixier and a simple linear regression between the logarithms of permeability and porosity. We have used 100% of the permeability–porosity data to obtain the predictor equations in each case. The best fit, in terms of the root mean-square error, was obtained with the statistical approach. The results obtained from the fractal model, the Tixier equation or the linear approach do not improve the neuro-fuzzy results. We have also randomly taken 25% of the porosity data to obtain the predictor equations. The increase of the input data density for the neuro-fuzzy approach improves the results, as is expected for a statistical analysis. On the contrary, for the physical model based on the fractal theory, the decrease in the data density could allow reaching the ideal theoretical Kozeny–Carman model, on which are based the fractal equations, and hence, the permeability prediction using these expressions is improved.