首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   36篇
  免费   2篇
  国内免费   1篇
测绘学   2篇
地球物理   19篇
地质学   5篇
海洋学   2篇
自然地理   11篇
  2022年   1篇
  2020年   4篇
  2019年   2篇
  2018年   3篇
  2017年   1篇
  2016年   4篇
  2015年   10篇
  2014年   3篇
  2008年   2篇
  2007年   1篇
  2005年   1篇
  2003年   1篇
  2001年   1篇
  1998年   2篇
  1997年   1篇
  1992年   1篇
  1991年   1篇
排序方式: 共有39条查询结果,搜索用时 0 毫秒
31.
32.
Urban heat island (UHI) effect is among the most typical characteristics of urban climate. The analysis of surface UHI (SUHI) mechanisms has received the most extensive attention in the world. Here, we quantify the diurnal and seasonal SUHI intensity (SUHII) in global 419 major cities during the period 2003-2013. A geographically weighted regression (GWR) was established to assess the relationships between SUHII and several driving factors, and it further was compared to the ordinary least square (OLS) and stepwise multiple linear regression (SMLR) models. We show that GWR model has higher determination coefficient (R2) than OLS and SMLR models (Time: summer daytime, summer night, winter daytime and winter nighttime; GWR: 0.805, 0.458, 0.699 and 0.582; OLS: 0.732, 0.347, 0.473 and 0.320; SMLR: 0.732, 0.341, 0.468 and 0.316), indicating the spatially non-stationarity in the relationships. During the day, both vegetation activity and tree cover fraction have stronger cooling effect on SUHI in the summer of Asia. At night, there are stronger albedo effects on SUHI in the summer of Eastern Asia and Western North America and in the winter of Eastern Asia. Furthermore, temperature has stronger effect on daytime SUHI in Africa, Europe and South America in summer, and precipitation has stronger effect on nighttime SUHI in Africa and Europe in summer. Our results emphasize the spatial variation of the relationships between SUHII and relevant driving factors across global major cities, further indicating that the spatially non-stationary effect of driving factors on SUHII need to be considered in the future.  相似文献   
33.
ABSTRACT

Geographically weighted regression (GWR) is a classic and widely used approach to model spatial non-stationarity. However, the approach makes no precise expressions of its weighting kernels and is insufficient to estimate complex geographical processes. To resolve these problems, we proposed a geographically neural network weighted regression (GNNWR) model that combines ordinary least squares (OLS) and neural networks to estimate spatial non-stationarity based on a concept similar to GWR. Specifically, we designed a spatially weighted neural network (SWNN) to represent the nonstationary weight matrix in GNNWR and developed two case studies to examine the effectiveness of GNNWR. The first case used simulated datasets, and the second case, environmental observations from the coastal areas of Zhejiang. The results showed that GNNWR achieved better fitting accuracy and more adequate prediction than OLS and GWR. In addition, GNNWR is applicable to addressing spatial non-stationarity in various domains with complex geographical processes.  相似文献   
34.
Time-frequency analysis of magnetotelluric data   总被引:1,自引:0,他引:1  
  相似文献   
35.
Statistical tests for whether some coefficients really vary over space play an important role in using the geographically weighted regression (GWR) to explore spatial non-stationarity of the regression relationship. In view of some shortcomings of the existing inferential methods, we propose a residual-based bootstrap test to detect the constant coefficients in a GWR model. The proposed test is free of the assumption that the model error term is normally distributed and admits some useful extensions for identifying more complicated spatial patterns of the coefficients. Some simulation with comparison to the existing test methods is conducted to assess the test performance, including the accuracy of the bootstrap approximation to the null distribution of the test statistic, the power in identifying spatially varying coefficients and the robustness to collinearity among the explanatory variables. The simulation results demonstrate that the bootstrap test works quite well. Furthermore, a real-world data set is analyzed to illustrate the application of the proposed test.  相似文献   
36.
利用小波多分辨率分析将地震动加速度分解为多频段小波分量,并运用复模态方法推导其计算层间隔震体系在地震作用下的动力响应公式,讨论各频段地震信号及结构响应的能量分配。同时利用小波时频工具分析地震动能量在时频域内的分布对层间隔震结构响应的影响,进而为考察地震动非平稳性对层间隔震结构非线性分析的影响提供方法。利用小波分析的以上优势,对一典型层间隔震结构分别进行弹性和弹塑性分析,结果表明弹性体系在地震作用下的响应可由该地震波各小波分量的响应叠加而得,地震动能量在时间上的集中会对层间隔震结构响应产生不利影响。  相似文献   
37.
利用小波重构合成地震波方法及特性研究   总被引:1,自引:0,他引:1       下载免费PDF全文
针对傅里叶变换合成地震波理论的不足,提出一种利用小波重构合成地震波的方法. 以控制频带能量为标准,推导了合成地震波的公式. 运用抗震设计规范中的相关设计参数合成了地震波,并分析研究了在合成地震波时小波函数基的选取方法和阻尼比对合成结果的影响. 结果表明,用小波重构合成的地震波能够反应地震波基本特性和场地特征周期,并具有很好的时频非平稳性.   相似文献   
38.
Nott  J. 《Natural Hazards》2003,30(1):43-58
Natural hazards are normally viewed as events that occur randomly overtime. This precept usually forms the basis for the development of the hazardmagnitude-recurrence interval relationship used in risk assessments. However,hazard variability does not always conform to this relationship especially overlonger time intervals. Non-stationarity can be common with some hazards andthose periods where the variability and/or mean (magnitude/frequency) remainconstant are referred to here as hazard regimes. Shifts from one regime to anotheroccur at a variety of time scales from centuries to millennia. Regime shifts areoften only discernible by examining longer-term records which usually includeprehistoric data. Risk assessments frequently ignore these regime shifts andestimates of the risks associated with tropical cyclones, tsunami, terrestrialfloods and landslides in Australia have been both under-estimated and exaggeratedwhen such assessments have been based solely upon short historical records.Examples of these regime shifts and their significance for natural hazard riskassessment are presented here.  相似文献   
39.
Abstract

An HBV rainfall–runoff model was applied to test the influence of climatic characteristics on model parameter values. The methodology consisted of the calibration and cross-validation of the HBV model on a series of 5-year periods for four selected catchments (Axe, Kamp, Wieprz and Wimmera). The model parameters were optimized using the SCEM-UA method which allowed for their uncertainty also to be assessed. Nine climatic indices were selected for the analysis of their influence on model parameters, and divided into water-related and temperature-related indices. This allowed the dependence of HBV model parameters on climate characteristics to be explored following their response to climate change conditioned on the catchment’s physical characteristics. The Pearson correlation coefficient and weighted Pearson correlation coefficient were used to test the dependence. Most parameters showed a statistically significant dependence on several climatic indices in all catchments. The study shows that the results of the correlation analysis with and without parametric uncertainty taken into account differ significantly.  相似文献   
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号