一种多因子相关计算方法   总被引：4，自引：0，他引：4  

陈乐湘  钮本良  陆宝宏  裘庆芗 《水文》2002,22(4):22-24

采用分析与图解相结合的方法解决多因子非线性相关计算,求回归方程问题。先从多个因子中找出对倚变量影响最大的一个因子,作单相关曲线,求残差;再从余下的因子中找出对残差影响最大的因子,作相关曲线,求残差,直到剩余各因子对残差影响相当;最后用剩余因子线性分解残差,从而求得多因子非线性回归方程。  相似文献   

泉水动态分析预测和资源评价——以辉县百泉为例   总被引：6，自引：2，他引：6  

姜宝良  付北锋  赵延涛 《水文地质工程地质》2002,29(3):43-46

本文通过对辉县百泉泉水流量动态的分析，确定了泉水流量动态的影响因素，建立了泉水流量的衰减方程和泉水流量的预测模型，预测了天然状态泉水流量，评了泉域岩溶水的开采资源。  相似文献   

基于正交设计的复杂坝基弹塑性力学参数反演   总被引：8，自引：1，他引：8  

陈益峰  周创兵 《岩土力学》2002,23(4):450-454

复杂坝基弹塑性力学参数反演的计算工作量直接取决于采用何种优化方法。根据大坝在运行期的实测资料，运用有限元正交数值试验、回归分析和优化相结合的方法，反演了坝基岩体的弹塑性力学参数。实例研究表明了该方法的有效性和实用性。  相似文献   

基于前传式网络逼近的太平洋副热带高压活动的诊断预测   总被引：13，自引：1，他引：13  

张韧 《大气科学》2001,25(5):650-660

基于前传式神经网络BP算法(BackpropagationNeuralNetwork)和回归模型,探讨了西太平洋副高面积指数同赤道东太平洋海温及赤道纬向风之间非线性分类和映射逼近的建模方法和效果比较.结果表明,前传式网络,特别是回归网络预报模型具有较好拟合精度和预报效果及比较实用的预报时效.  相似文献   

区域趋势控制协变量回归分析效果评估方法研究   总被引：10，自引：1，他引：10  

叶家东  李铁林 《气象科学》2001,21(1):64-72

本文根据区域趋势控制和气象－物理协变量相关设计了三套非随机化人工增雨作业效果评估方案，个例作用区域趋势对比双比分析评估方案，区域趋势相关回归分析评估方案和气象－物理协变量多元回归分析评估方案，对河南省实例评估计算表明，利用物理协变量作为控制因子，可以提高作业区自然水量估计值的准确度，从而能提高随机化作业的效果评估效率。  相似文献   

1998/2000年ENSO冷事件过程诊断   总被引：5，自引：5，他引：5  

李晓燕 《热带气象学报》2001,17(1):90-96

通过对1998／2000年ENSO冷事件发展过程的诊断分析，揭示了这次事件爆发快、强度较大、结束时东太平洋海温变化突然，大气响应滞后等特点。通过与其它冷事件特征的比较，着重分析了冷事件爆发前期次表层海温及大气风场的演变特征，指出次表层冷水异常的发展和东移是本次冷事件爆发的基本条件，大气风场特征对冷事件的形成和加强起着关键作用，同时冷事件和爆发季节对事件的长度和强度有着非常重要的影响。  相似文献   

兰州市冬季空气污染的天气成因分析及浓度预报   总被引：9，自引：0，他引：9  

王宝鉴  许东蓓  蒲彦玲  王鹏祥  王锡稳 《干旱气象》2001,19(4):18-21

兰州是全国冬季大气污染最严重的城市之一 ,通过对污染与天气形势的分析 ,给出了影响冬季兰州污染的天气分型 ;对 3种主要空气污染物TSP、SO2 、NOX 浓度值与同期表征逆温特征的逆温参数及地面气象要素作了统计分析 ,结果表明 :(1)污染物浓度与逆温层厚度呈显著正相关 ;(2 )污染物浓度与平均温度、能见度、风速、总云量、相对湿度成负相关 ,与温差、气压成正相关。最后针对不同天气分型 ,给出了冬半年兰州污染物浓度预报方程 ,经检验预报效果良好  相似文献   

Application of GIS Processing Techniques for Producing Mineral Prospectivity Maps—A Case Study: Mesothermal Au in the Swayze Greenstone Belt,Ontario, Canada   总被引：1，自引：0，他引：1  

Harris  J. R.  Wilkinson  L.  Heather  K.  Fumerton  S.  Bernier  M. A.  Ayer  J.  Dahn  R. 《Natural Resources Research》2001,10(2):91-124

A Geographic Information System (GIS) is used to prepare and process digital geoscience data in a variety of ways for producing gold prospectivity maps of the Swayze greenstone belt, Ontario, Canada. Data used to produce these maps include geologic, geochemical, geophysical, and remotely sensed (Landsat). A number of modeling methods are used and are grouped into data-driven (weights of evidence, logistic regression) and knowledge-driven (index and Boolean overlay) methods. The weights of evidence (WofE) technique compares the spatial association of known gold prospects with various indicators (evidence maps) of gold mineralization, to derive a set of weights used to produce the final gold prospectivity map. Logistic regression derives statistical information from evidence maps over each known gold prospect and the coefficients derived from regression analysis are used to weight each evidence map. The gold prospectivity map produced from the index overlay process uses a weighting scheme that is derived from input by the geologist, whereas the Boolean method uses equally weighted binary evidence maps.The resultant gold prospectivity maps are somewhat different in this study as the data comprising the evidence maps were processed purposely differently for each modeling method. Several areas of high gold potential, some of which are coincident with known gold prospects, are evident on the gold prospectivity maps produced using all modeling methods. The majority of these occur in mafic rocks within high strain zones, which is typical of many Archean greenstone belts.  相似文献   

Maximum likelihood environmental calibration and the compute program WACALIB a correction     

H.J.B. Birks 《Journal of Paleolimnology》2001,25(1):111-115

A recently discovered error in the part of the computer program WACALIB that implements maximum likelihood (ML) calibration has been discovered and corrected. The new version of WACALIB has been re-run with all the data-sets from which results based on the earlier version of WACALIB had been published. The new results suggest that ML regression and calibration perform as well or even better than weighted averaging (WA), at least when judged by the apparent root mean squared error. Further work involving cross-validation is required to evaluate more fully the relative performance of WA and ML approaches.  相似文献   

Thematic Map Analysis Using Multiple Regression     

James C. Brower  Daniel F. Merriam 《Mathematical Geology》2001,33(3):353-368

Thematic maps can be analyzed by multiple regression for (1) forward prediction where a younger geological structural map is written as a least-squares function of older maps for information on historical perspectives or (2) by backward prediction where an older map is regressed stepwise on a series of younger ones to aid in prospecting. The technique was evaluated by a series of structure maps on different geological horizons from the U.S. Midcontinent (Kansas) where the forward prediction proved more effective than backward. In forward prediction, the first map entered into a multiple regression is invariably the immediately underlying one as expected. On the other hand, the first map in a backward prediction is not necessarily related to stratigraphy which limits the utility of the technique for prospecting.  相似文献