新丰江库区上地壳三维细结构层析成像   总被引：5，自引：2，他引：3       下载免费PDF全文

杨卓欣  刘宝峰  王勤彩  赵翠萍  陈章立  张先康 《地球物理学报》2013,56(4):1177-1189

在新丰江库区布设一个范围约50 km×40 km、由50个地震临时台站组成的观测台阵,接收来自不同方位的人工震源产生的莫霍界面反射波;台阵中的20个台站和5个区域固定台还对2009年3月至2010年5月发生在库区的地方震进行了观测.本文联合利用人工地震莫霍面反射波走时和天然地震直达波走时,采用连续模型反演技术重建了库区上地壳P波、S波慢度扰动和V_p/V_s扰动分布图像.研究结果表明:新丰江库区东、西部地区上地壳结构存在明显的差异.库区东部地区构造复杂,多条断裂在该区呈交叉状分布.北西向的石角-新港-白田断裂带在库区段内具有复杂的岩性和构造特征,该断裂带在新港至双塘一线可能延伸至地下8 km左右;近北东向的断裂带切割地壳较深.峡谷区及大坝以东附近地区存在上、下贯通的波速比高值区,尤其是大坝以西的深水峡谷区,存在一条顺河走向的陡倾角断层裂隙带,为库水渗透提供了良好通道.库区西部地区为相对稳定构造区,完整坚硬的花岗岩体透水性能较差,受库水渗透影响很小.新丰江水库诱发地震的形成与深部构造环境密切相关.峡谷区及大坝以东附近地区上地壳介质性质呈现明显的横向不均匀性,微震分布在介质物性结构的特定部位,"软"、"硬"交错的介质环境是倾滑正断层型微小震产生的可能原因.  相似文献   

Artificial neural networks and nonlinear regression techniques to assess the influence of slake durability cycles on the prediction of uniaxial compressive strength and modulus of elasticity for carbonate rocks   总被引：1，自引：0，他引：1  

S. Yagiz  E. A. Sezer  C. Gokceoglu 《国际地质力学数值与分析法杂志》2012,36(14):1636-1650

Understanding rock material characterizations and solving relevant problems are quite difficult tasks because of their complex behavior, which sometimes cannot be identified without intelligent, numerical, and analytical approaches. Because of that, some prediction techniques, like artificial neural networks (ANN) and nonlinear regression techniques, can be utilized to solve those problems. The purpose of this study is to examine the effects of the cycling integer of slake durability index test on intact rock behavior and estimate some rock properties, such as uniaxial compressive strength (UCS) and modulus of elasticity (E) from known rock index parameters using ANN and various regression techniques. Further, new performance index (PI) and degree of consistency (Cd) are introduced to examine the accuracy of generated models. For these purposes, intact rock dataset is established by performing rock tests including uniaxial compressive strength, modulus of elasticity, Schmidt hammer, effective porosity, dry unit weight, p‐wave velocity, and slake durability index tests on selected carbonate rocks. Afterward, the models are developed using ANN and nonlinear regression techniques. The concluding remark given is that four‐cycle slake durability index (I_d4) provides more accurate results to evaluate material characterization of carbonate rocks, and it is one of the reliable input variables to estimate UCS and E of carbonate rocks; introduced performance indices, both PI and Cd, may be accepted as good indicators to assess the accuracy of the complex models, and further, the ANN models have more prediction capability than the regression techniques to estimate relevant rock properties. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

Evaluation of classifiers for processing Hyperion (EO-1) data of tropical vegetation     

Dhaval Vyas  N.S.R. Krishnayya  K.R. Manjunath  S.S. Ray  Sushma Panigrahy 《International Journal of Applied Earth Observation and Geoinformation》2011

There is an urgent necessity to monitor changes in the natural surface features of earth. Compared to broadband multispectral data, hyperspectral data provides a better option with high spectral resolution. Classification of vegetation with the use of hyperspectral remote sensing generates a classical problem of high dimensional inputs. Complexity gets compounded as we move from airborne hyperspectral to Spaceborne technology. It is unclear how different classification algorithms will perform on a complex scene of tropical forests collected by spaceborne hyperspectral sensor. The present study was carried out to evaluate the performance of three different classifiers (Artificial Neural Network, Spectral Angle Mapper, Support Vector Machine) over highly diverse tropical forest vegetation utilizing hyperspectral (EO-1) data. Appropriate band selection was done by Stepwise Discriminant Analysis. The Stepwise Discriminant Analysis resulted in identifying 22 best bands to discriminate the eight identified tropical vegetation classes. Maximum numbers of bands came from SWIR region. ANN classifier gave highest OAA values of 81% with the help of 22 selected bands from SDA. The image classified with the help SVM showed OAA of 71%, whereas the SAM showed the lowest OAA of 66%. All the three classifiers were also tested to check their efficiency in classifying spectra coming from 165 processed bands. SVM showed highest OAA of 80%. Classified subset images coming from ANN (from 22 bands) and SVM (from 165 bands) are quite similar in showing the distribution of eight vegetation classes. Both the images appeared close to the actual distribution of vegetation seen in the study area. OAA levels obtained in this study by ANN and SVM classifiers identify the suitability of these classifiers for tropical vegetation discrimination.  相似文献   

Imaging spectroscopy in soil-water based site suitability assessment for artificial regeneration to Scots pine     

Maarit Middleton  Paavo Nrhi  Raimo Sutinen 《ISPRS Journal of Photogrammetry and Remote Sensing》2011,66(3):287-297

In a humid northern boreal climate, the success rate of artificial regeneration to Scots pine (Pinus sylvestris L.) can be improved by including a soil water content (SWC) based assessment of site suitability in the reforestation planning process. This paper introduces an application of airborne visible-near-infrared imaging spectroscopic data to identify suitable subregions of forest compartments for the low SWC-tolerant Scots pine. The spatial patterns of understorey plant species communities, recorded by the AISA (Airborne Imaging Spectrometer for Applications) sensor, were demonstrated to be dependant on the underlying SWC. According to the nonmetric multidimensional scaling and correlation results twelve understorey species were found to be most abundant on sites with high soil SWCs. The abundance of bare soil, rocks and abundance of more than ten species indicated low soil SWCs. The spatial patterns of understorey are attributed to time-stability of the underlying SWC patterns. A supervised artificial neural network (radial basis functional link network, probabilistic neural network) approach was taken to classify AISA imaging spectrometer data with dielectric (as a measure volumetric SWC) ground referencing into regimes suitable and unsuitable for Scots pine. The accuracy assessment with receiver operating characteristics curves demonstrated a maximum of 74.1% area under the curve values which indicated moderate success of the NN modelling. The results signified the importance of the training set’s quality, adequate quantity (>2.43 points/ha) and NN algorithm selection over the NN algorithm training parameter optimization to perfection. This methodology for the analysis of site suitability of Scots pine can be recommended, especially when artificial regeneration of former mixed wood Norway spruce (Picea abies L. Karst) - downy birch (Betula pubenscens Ehrh.) stands is being considered, so that artificially regenerated areas to Scots pine can be optimized for forestry purposes.  相似文献   

Do benthic biofilters contribute to sustainability and restoration of the benthic environment impacted by offshore cage finfish aquaculture?     

Aguado-Giménez F  Piedecausa MA  Carrasco C  Gutiérrez JM  Aliaga V  García-García B 《Marine pollution bulletin》2011,62(8):1714-1724

Benthic biofilters were deployed under a cage fish farm and in two reference locations to assess the influence of the farm on the biofilters and the surroundings, as well as to verify the usefulness of this technology as a mitigation tool. The biofilters underneath the farm recruited a fouling community practically identical to that of the control biofilters, which included a variety of trophic strategies. The former showed a higher ¹⁵N enrichment, indicating that fouling beneath the farm was benefiting from the farm waste. The waste retention efficiency was low (0.02 g N m⁻² month⁻¹) beneath the farm. Benthic biofilters aggregated demersal wild fish around and within them. Pelagic wild fish also frequently used the biofilters beneath the farm, forming compact shoals around them. The increased complexity of the habitat below the fish farm enhanced biodiversity, but this improvement did not lead to the recovery of the sediments around the biofilters.  相似文献   

基于MATLAB神经网络方法的多层砖房震害预测   总被引：1，自引：0，他引：1       下载免费PDF全文

姜伟  马令勇  刘功良 《地震工程学报》2011,33(2):155-158

提出利用MATLAB人工神经网络工具箱建立基于贝叶斯正则算法的BP神经网络模型,以地震区多层砖房震害调查数据为因子的震害预测方法.神经网络模型输入震害因子包括建筑的层数、施工质量、房屋整体性等,输出值为建筑物在地震作用下的破坏程度.结果表明,本方法可以对多层砖房的震害样本进行预测并达到较理想的效果.  相似文献   

聊古1井在不同取水模式下气体观测效果的对比分析     

李月强  王华  刘保华  连凯旋  崔娜  孙丕锋  冯恩国  赵杰锋 《中国地震》2011,27(2):192-198

为解决聊古1井断流问题,聊城地震水化试验站先后引进、开发了人工激发引流观测技术和潜水泵变频稳流抽水技术.对天然自流观测系统、人工激发引流观测系统和潜水泵变频稳流抽水观测系统等3种不同取水模式下产出的气体观测数据进行一致性分析.结果表明,人工激发引流观测系统下气体观测动态特征年变比较明显,潜水泵变频稳流抽水观测系统下气体观测动态特征与天然自流状态下的动态特征基本一致.  相似文献   

Artificial neural network forward modelling and inversion of electrokinetic logging data     

N. Ardjmandpour  C. Pain  J. Singer  J. Saunders  E. Aristodemou  J. Carter 《Geophysical Prospecting》2011,59(4):721-748

An artificial neural network method is proposed as a computationally economic alternative to numerical simulation by the Biot theory for predicting borehole seismoelectric measurements given a set of formation properties. Borehole seismoelectric measurements are simulated using a finite element forward model, which solves the Biot equations together with an equation for the streaming potential. The results show that the neural network method successfully predicts the streaming potentials at each detector, even when the input pressures are contaminated with 10% Gaussian noise. A fast inversion methodology is subsequently developed in order to predict subsurface material properties such as porosity and permeability from streaming potential measurements. The predicted permeability and porosity results indicate that the method predictions are more accurate for the permeability predictions, with the inverted permeabilities being in excellent agreement with the actual permeabilities. This approach was finally verified by using data from a field experiment. The predicted permeability results seem to predict the basic trends in permeabilities from a packer test. As expected from synthetic results, the predicted porosity is less accurate. Investigations are also carried out to predict the zeta potential. The predicted zeta potentials are in agreement with values obtained through experimental self potential measurements.  相似文献   

Variation of bacteria biomass and its possible controlling factors in the East China Sea     

Wenjuan Xia  Jiangtao Wang  Liju Tan  Qiulu Wang 《中国海洋大学学报(英文版)》2011,10(2):135-141

Two surveys were performed for determining bacteria biomass (BB), temperature, salinity, chlorophyll a (chl-a) and nutrient concentrations at 11 stations with three sampling depths in the high-incidence regions of red tide in the East China Sea (ECS) in the spring of 2006. Temperature and salinity increased from nearshore to offshore region and from high latitude to low latitude in the two cruises of 2006. BB were between 0.3–5.2 mgC m⁻³ (about 2.1 mgC m⁻³ on average) and 0.2–6.0 mgC m⁻³ (about 2.7 mgC m⁻³ on average) respectively in the two cruises. BB in the surface layer decreased from the Changjiang River estuary to high sea and from low latitude to high latitude. The results showed that bacterial growth was regulated by temperature, primary production and inorganic nutrient concentrations depending on different hydrographic conditions. In the surface and middle layers where the primary production can supply enough organic substrate, temperature was the main factor to control bacteria biomass. BB showed a good correlation between the surface and middle layers in both cruises. The distribution of nutrients during both cruises showed a similar decreasing trend from nearshore region and high latitude to offshore region and low latitude. High BB values were mainly recorded from samples in the middle layer where chl-a concentrations were also high, indicating primary production being strongly correlated with temperature over the ECS shelf. In the offshore area, phosphate and silicate became limiting factors for phytoplankton growth with indirect influence on BB. Bacteria played an important role in nitrogen regeneration process turning organic nitrogen to inorganic forms such as NH₄ ⁺. The increasing ratio of NH₄ ⁺/DIN could be a proof of that.  相似文献   

A neurocomputing approach to the forecasting of monthly maximum temperature over Kolkata, India using total ozone concentration as predictor     

Syam Sundar De  Goutami Chattopadhyay  Bijoy Bandyopadhyay  Suman Paul 《Comptes Rendus Geoscience》2011,343(10):664-676

The association between the monthly total ozone concentration and monthly maximum temperature over Kolkata (22.56° N, 88.30° E), India, has been explored in this paper. For this, the predictability of monthly maximum temperature based on the total ozone as predictor is investigated using Artificial Neural Network. The presence of persistence and similar cyclic patterns are revealed through autocorrelation and cross-correlation coefficients. Common cycles of length 12 and 6 have been identified through periodogram. Hence, a predictive model has been generated by Artificial Neural Network in the form of Multi Layer Perceptron (MLP) using scaled conjugate gradient learning with sigmoid non-linearity. After training and testing the network, an MLP with total ozone of month n as predictor and maximum temperature of month (n + 1) as the target output is found as the best model. Performance of the model has been judged statistically. Finally, the MLP model has been compared with linear and non-linear regressions and the efficiency of MLP has been established over the regression models.  相似文献