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41.
粒子群优化算法是基于群智能的随机全局优化方法,它源于对鸟群简化社会系统的模拟。为了提高标准粒子群优化算法的收敛性能,将生物免疫系统的记忆能力和多样性引入标准粒子群优化算法,提出一种免疫粒子群优化算法。在提取纹理样本Laws纹理能量模板特征、小波特征等纹理特征的基础上,提出针对分类问题的粒子表达方法和群体寻优策略,实现了基于免疫粒子群算法的纹理分类。实验结果表明,与标准粒子群优化算法相比,免疫粒子群优化算法在获取训练样本类别中心时具有较好的收敛性能,并且基于该算法的影像纹理分类具有较高的分类精度。  相似文献   
42.
因子分类法在黑龙江塔河地区地质填图中的应用   总被引:1,自引:0,他引:1  
利用因子分类法在黑龙江塔河地区进行地球化学单元识别,根据各单元的理论地球化学意义及其与地质单元的对应关系,进行浅覆盖区地质填图研究。充分提取区域化探资料中的地球化学信息,将研究区识别为具有特定地质、地球化学意义的5个地球化学单元。其中:Be、Nb、Sn、Y、Rb单元主要反映研究区古生代花岗岩和中生代酸碱性火山岩的分布;Co、TFe、Cr、Ni、V、Ti、MgO单元主要反映研究区早元古代侵入岩、变质岩和古生代基性岩体的分布;SiO2、K2O、Na2O单元反映的地质单元主要为古生代侵入岩、中生代酸碱性火山岩和沉积岩;Al2O3、Li、F单元主要反映中生代火山岩的分布;CaO、Sr、Ba单元反映的是中生代沉积岩,可能与生物沉积作用有关,代表比较稳定的沉积环境。同时,根据不同单元的分布形态和边界走向,识别和推断了研究区的北东、北西、南北及东西向断裂构造。  相似文献   
43.
根据主采煤层顶底板岩体岩性类型及结构面发育程度对其稳定性进行了评价:72煤层顶板以中等稳定一不稳定类型为主,82煤层顶板以中等稳定类型为主,10煤层顶板以中等稳定一稳定类型为主。在大量统计见煤点硬质岩百分含量(k值)的基础上,结合顶板岩石的单轴抗压强度,对各主采煤层顶底板工程地质类型进行了划分:72煤层以一、二类顶板为主,82、10煤层均以五类顶板为主。综合评价该矿工程地质条件为中等即Ⅲ类二型。根据研究成果,指出该矿在采掘过程中可能出现的工程地质问题,并依此提出了治理建议。  相似文献   
44.
Hash表技术是流分类的常用方法之一,用Hash表技术实现快速流分类的关键问题是降低冲突率,提高冲突解决的效率。该文通过提出几个新的概念(如发散、最佳流分类比特和相似比特等)来降低冲突率,通过提出查找树方案来提高冲突解决的效率,从而得到了一种能适应进行任意域流分类工作的、高效的流分类哈希(Efficient Packet Classification Hash,EPCH)表技术方案。仿真试验证明:该方案冲突率低、效率高,值得推广。  相似文献   
45.
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   
46.
华北地台晚古生代含煤地层多重划分   总被引:11,自引:0,他引:11  
以60个大体均匀分布于华北地台的地层剖面为基础,以晚古生代聚煤盆地的整体性为依托,对华北晚古生代地层进行多重划分研究,在岩石地层方面,研究了地层分区、划分了18个岩石地层单位“组”,分析了组的穿时性,在生物地层方面,重点介绍了蜒、古植物和孢粉生物地层,划分了各个组合带、延限带和顶峰带,分析了生物演化系列,空间展布和对比,提出了多方面的新认识,在年代地层方面,应用界线层型概念以及与首要门类生物地层单  相似文献   
47.
Seismic hazard of Egypt   总被引:1,自引:0,他引:1  
Earthquake hazard parameters such as maximum expected magnitude,M max, annual activity rate,, andb value of the Gutenberg-Richter relation have been evaluated for two regions of Egypt. The applied maximum likelihood method permits the combination of both historical and instrumental data. The catalogue used covers earthquakes with magnitude 3 from the time interval 320–1987. The uncertainties in magnitude estimates and threshold of completeness were taken into account. The hazard parameter determination is performed for two study areas. The first area, Gulf of Suez, has higher seismicity level than the second, all other active zones in Egypt.b-values of 1.2 ± 0.1 and 1.0 ± 0.1 are obtained for the two areas, respectively. The number of annually expected earthquakes with magnitude 3 is much larger in the Gulf of Suez, 39 ± 2 than in the other areas, 6.1 ± 0.5. The maximum expected magnitude is calculated to be 6.5 ± 0.4 for a time span of 209 years for the Gulf of Suez and 6.1 ± 0.3 for a time span of 1667 years for the remaining active areas in Egypt. Respective periods of 10 and 20 years were reported for earthquakes of magnitude 5.0 for the two subareas.  相似文献   
48.
Multivariate statistical analyses have been extensively applied to geochemical measurements to analyze and aid interpretation of the data. Estimation of the covariance matrix of multivariate observations is the first task in multivariate analysis. However, geochemical data for the rare elements, especially Ag, Au, and platinum-group elements, usually contain observations the below detection limits. In particular, Instrumental Neutron Activation Analysis (INAA) for the rare elements produces multilevel and possibly extremely high detection limits depending on the sample weight. Traditionally, in applying multivariate analysis to such incomplete data, the observations below detection limits are first substituted, for example, each observation below the detection limit is replaced by a certain percentage of that limit, and then the standard statistical computer packages or techniques are used to obtain the analysis of the data. If a number of samples with observations below detection limits is small, or the detection limits are relatively near zero, the results may be reasonable and most geological interpretations or conclusions are probably valid. In this paper, a new method is proposed to estimate the covariance matrix from a dataset containing observations below multilevel detection limits by using the marginal maximum likelihood estimation (MMLE) method. For each pair of variables, sayY andZ whose observations containing below detection limits, the proposed method consists of three steps: (i) for each variable separately obtaining the marginal MLE for the means and the variances, , , , and forY andZ: (ii) defining new variables by and and lettingA=C+D andB=CD, and obtaining MLE for variances, and forA andB; (iii) estimating the correlation coefficient YZ by and the covariance YZ by . The procedure is illustrated by using a precious metal geochemical data set from the Fox River Sill, Manitoba, Canada.  相似文献   
49.
Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (Xn, n 0) or (Xt, t 0) for which the parameters are of interest and physically meaningful, and an observable process (Yn, n 0) or (Yt, t 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points.  相似文献   
50.
This paper presents the results of engineering geological investigations and tunnel support design studies, carried out at the Sulakyurt dam site, northeast of Ankara, Turkey. The Sulakyurt dam will be used for flow control and water storage for irrigation projects. Studies were carried out both in the field and the laboratory. Field studies include engineering geological mapping, intensive discontinuity surveying, core drilling and sampling for laboratory testing. The diversion tunnel will be driven in rock mass, consisting of granite and diorite. Empirical, analytical and numerical methods were combined for safe tunnel design. Rock mass rating (RMR), Rock mass quality (Q) and Geological strength index (GSI) systems were used for empirical rock mass quality determination, site characterization and support design. The convergence–confinement method was used as analytical method and software called Phase2, a 2D finite element program, was utilized as numerical method. According to the results acquired from the empirical, analytical and numerical methods, tunnel stability problems were expected in both granite and diorite rock masses. The support system, suggested by empirical methods, was applied and the performance of suggested support system was evaluated by means of numerical modelling. It was concluded that the suggested support systems were adequate, since after applying the suggested support system to granite and diorite, tunnel deformation and the yielded elements around the tunnel decreased significantly. Thus, it is suggested that for more reliable support design empirical, numerical and analytical methods should be combined.  相似文献   
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