Automatic classification of volcanic earthquakes by using Multi-Layered neural networks     

S. Falsaperla  S. Graziani  G. Nunnari  S. Spampinato 《Natural Hazards》1996,13(3):205-228

The application of neural networks as classifiers of seismic events is described with the aim of developing an automatic system for the classification of explosion quakes at the Stromboli volcano. The architecture of the network that we trained to identify four different classes of shocks was a Multi-Layer Perceptron, using the Back Error Propagation algorithm. Five different approaches for representing the information embedded in the seismograms, both in the time and in the frequency domain, were considered, and the results compared. The direct use of the time series of the shocks was not satisfactory. The auto-correlation function worked well, but in some cases it was misleading. A better performance was obtained with a frequency domain representation. Finally, the use of the envelope function did not work well. Combining parameters such as the auto-correlation and envelope functions can improve one source of error, but it may introduce new ones. The performance obtained highlights the importance of the data attributes used for the training of the network. Topologies with eight neurons in a single hidden layer gave, on average, the best results among the considered neural network structures. The overall results provide a large number of events (89% with the best performance) correctly classified, indicating that this automatic technique is reliable, and encouraging further applications in the field of volcanic seismology.  相似文献   

人工神经网络在白云岩类型识别中的应用     

蔡煜东  姚林声 《岩石矿物学杂志》1994,13(1):51-54

利用地球化学数据,运用人工神经网络方法对美国密苏里州东南Ｂｏｎｎｅｔｅｒｒｅ组（寒武纪）滨海相的白云岩进行了分类、识别,判别率达１００％,结果表明,该方法性能良好,可望成为岩石分类、判别的有效手段。  相似文献   

The developmental characteristics and strategic ideas of urbanization in China     

辜胜阻 《中国地理科学(英文版)》1993,3(2):97-111

Since cities and towns are places where those nonagricultural industries are centralized, urbanization is greatly interrelated with industrialization and de-agriculturalization. By means of this kind of interrelationship, Chinese urbanization level may be estimated with the formulas: P1=I1/I0/u0, Pr = N1/N0/u0. The urbanization after the founding of the People's Republic of China can be divided into the following 5 stages: the stage at the out set of industrialization (1949-1957); the high-speed urbanization stage (1958-1960); the first counter-urbanization stage (1961-1965); the second counter-urbanization stage (1966-1976); and the high-speed urbanization stage (1978-now). The characteristics of Chinese urbanization are: the industrialization launched by the government; the simultaneous development of urbanization of cities and urbanization of rural areas; the quite low capability of urbanization to absorb nonagricultural labor force; the incoordinate development of cities, etc. Before establishing a  相似文献   

基于网络药理学与分子对接技术探讨青蛇方外用治疗湿疹的作用机制          下载免费PDF全文

王家辉  王军文  彭湘宁 《应用海洋学学报》2024,40(2):189

目的：基于网络药理学与分子对接技术探讨青蛇方外用治疗湿疹的作用机制。方法：应用TCMSP和UniProt数据库平台查询青蛇方组方的有效活性成分及靶基因,与疾病靶基因取交集后构建蛋白质-蛋白质相互作用(PPI)网络;应用DAVID数据库,对潜在核心作用靶点基因进行基因本体（GO）功能、京都基因与基因组百科全书（KEGG）通路富集分析。利用分子对接原理论证青蛇方生物活性成分与核心靶点的分子结合能力。结果：筛选出青蛇方有效成分63种,作用靶点99个;主要有β-谷甾醇、2,4,7-三羟基-9,10-二氢菲、靛蓝素、豆甾醇、色氨酸等关键成分;转录因子AP-1（JUN）、肿瘤坏死因子（TNF）、原癌基因（RELA）、干扰素γ（IFNG）、转化生长因子-β1（TGF-β1）等核心基因。关键信号通路有癌症信号通路、恰加斯病通路、弓形体病通路、脂质和动脉粥样硬化通路等,分子对接结果显示活性成分与核心靶点基因结合能力较强。结论：青蛇方外用可以通过多种活性成分、多种通路有效抑制免疫炎症反应,促进免疫系统正常运行,从而达到治疗湿疹的目的。  相似文献   

基于遥感影像大数据、卷积神经网络的福建省有效致灾雷电分布模型及应用     

张烨方  刘冰  冯真祯  朱彪 《气象科技》2021,49(6):953-959

为了研究福建省有效致灾雷电的分布情况，基于福建省2004—2012年闪电定位数据及雷击人员伤亡数据、福建省L17级谷歌遥感影像瓦片，引入卷积神经网络模型对遥感影像所在区域是否属于人员活动的属性进行建模、训练和预测，得到福建省人员活动属性的格点产品，结合福建省历史雷电数据对有效致灾的雷电分布情况进行了分析，结果表明：①设计的遥感影像+CNN识别模型具有一定的可行性和准确率，通过显著性水平为0.01的假设检验；②福建省有63.55%的格点为无人员活动区域；③平均有45.36%的闪电落在无人员活动的区域，因地制宜地对其他致灾闪电进行预警是提高应急减灾服务效果的可行途径；④有效致灾雷电密度与历史雷击人员伤亡数据的相关性远大于常规雷电密度与历史雷击人员伤亡数据的相关性，有效致灾雷电分布在表征雷电灾害上比常规雷电分布更具有指示意义。  相似文献   

Estimation of runoff distribution within river systems: Application to the Lena Basin (Siberia)     

N. Kosheleva  E. Karabanov  A. Kositskiy  D. Williams  S. Armstrong 《Journal of Geochemical Exploration》2006,88(1-3):118

A channel account approach is proposed to estimate longitudinal changes in runoff along large river systems. This new method provides a quantitative basis for describing the fluvial transport of suspended particulate material and dissolved substances. This method includes an evaluation of basic elements of water balance in separate sections of the river network and subsequent correction of channel accounting equations for the entire system using a maximum likelihood principle. To calculate water discharges of tributaries that have no hydrological information, structural analysis of river network is performed. This approach provides less error in comparison with traditional methods of estimating lateral inflow. The method is used to trace water discharge with increasing distance along the Lena river basin and to evaluate the contribution of geologically and lithologically uneven sub-basins in water discharge formation during a summer low water period.  相似文献   

Modèles géostatistiques de concentrations ou de débits le long des cours d'eau     

Chantal de Fouquet  Caroline Bernard-Michel 《Comptes Rendus Geoscience》2006,338(5):307-318

Estimating concentrations or flow rates along a stream network requires specific models. Two classes of models, recently proposed in the literature, are generalized, to the intrinsic case in particular. We present a global construction by ‘streams’, i.e. on the whole set of paths between sources and outlet. Combining stationary or intrinsic one-dimensional random functions leads to stationary or intrinsic models on segments, with discontinuities at the forks. A construction from outlet to sources, leads to stationary or intrinsic models on each stream, without any discontinuity at the forks. The linear variogram is found as a particular case. The extension to the linear model of coregionalization is immediate, allowing a multivariate modelling of concentrations. To cite this article: C. de Fouquet, C. Bernard-Michel, C. R. Geoscience 338 (2006).  相似文献   

基于GIS的山地林道网优化配置系统   总被引：1，自引：0，他引：1  

邱荣祖  兰樟仁  黎建明 《山地学报》2006,24(6):716-720

应用系统选择永安元沙国有林业采育场的部分林班为示范,建立森林资源空间数据库.以ARC/INFO为开发平台,以山地林道网理论为指导,应用G IS技术、DBMS技术与数学规划集成技术,使用AML语言进行二次开发设计山地林道网优化配置系统,实现计算机辅助林道网配置,提高决策的科学性。  相似文献   

Application of back-propagation networks in debris flow prediction   总被引：6，自引：0，他引：6  

Tung-Chueng Chang  Ru-Jen Chao   《Engineering Geology》2006,85(3-4):270-280

Debris flows have caused serious loss of human lives and a lot of damage to properties in Taiwan over the past decades. Moreover, debris flows have brought massive mud causing water pollution in reservoirs and resulted in water shortage for daily life locally and affected agricultural irrigation and industrial usages seriously. A number of methods for prediction of debris flows have been studied. However, the successful prediction ratio of debris flows cannot always maintain a stable and reliable level. The objective of this study is to present a stable and reliable analytical model for occurrence predictions of debris flows. This study proposes an Artificial Neural Networks (ANN) model that was constructed by seven significant factors using back-propagation (BP) algorithm. These seven factors include (1) length of creek, (2) average slope, (3) effective watershed area, (4) shape coefficient, (5) median size of soil grain, (6) effective cumulative rainfall, and (7) effective rainfall intensity. A total of 178 potential cases of debris flows collected in eastern Taiwan were fed into the ANN model for training and testing. The average ratio of successful prediction reaching 93.82% demonstrates that the presented ANN model with seven significant factors can provide a stable and reliable result for the prediction of debris flows in hazard mitigation and guarding systems.  相似文献   

Modeling the cyclic swelling pressure of mudrock using artificial neural networks     

M. Moosavi  M.J. Yazdanpanah  R. Doostmohammadi 《Engineering Geology》2006,87(3-4):178-194

The stochastic nature of the cyclic swelling behavior of mudrock and its dependence on a large number of interdependent parameters was modeled using Time Delay Neural Networks (TDNNs). This method has facilitated predicting cyclic swelling pressure with an acceptable level of accuracy where developing a general mathematical model is almost impossible. A number of total pressure cells between shotcrete and concrete walls of the powerhouse cavern at Masjed–Soleiman Hydroelectric Powerhouse Project, South of Iran, where mudrock outcrops, confirmed a cyclic swelling pressure on the lining since 1999. In several locations, small cracks are generated which has raised doubts about long term stability of the powerhouse structure. This necessitated a study for predicting future swelling pressure. Considering the complexity of the interdependent parameters in this problem, TDNNs proved to be a powerful tool. The results of this modeling are presented in this paper.  相似文献