基于免疫粒子群优化算法的影像纹理分类

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。     

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

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.     

Engineering geological studies and tunnel support design at Sulakyurt dam site, Turkey

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.     

Modeling of the classification behavior of the diaphragms used in multi-chamber cement mills

A new approach has been developed for describing the classification that arises at the diaphragm in multi-chamber ball mills. Fourteen industrial scale cement mills have been sampled in this study and after mass balancing, model fits of the equipment were done. Successive mill product predictions for the sampled conditions were achieved, and requirements to build up an optimization capable model are discussed.     

A Connectivity Index for Discrete Fracture Networks

Connectivity is an important measure for assessing flow transport in rock, especially through fractures. In this paper, rock fracture systems are modelled by a discrete fracture model simulated by a marked point process. A connectivity index is then introduced to quantify the connectivity between any two points in space. Monte Carlo simulation is used to evaluate the connectivity index for stationary cases and relationships between the connectivity index and the parameters of the discrete fracture model are analysed. The average number of intersections per fracture, X_f, and the fracture intensity, P12 (P32), are calculated and the relationships between these parameters and the connectivity index are investigated, concluding that X_f is the more suitable parameter for the classification of rock mass flow properties. The relationships between the connectivity index and the percolation state of the fractured medium are also discussed. An edge correction is briefly discussed and a practical example is used to demonstrate the method of computing the connectivity index.     

A Solution to the Problem of Predicting the Suitability of Silty–clayey Materials for Cement-stabilization

Major geotechnical problems in construction involving silty–clayey soils are due to their low strength, durability and high compressibility of soft soils, and the swell–shrink nature of the overconsolidated swelling soils. Confronted with these problems, a suitable ground improvement technique is needed, for deep excavations in soft clays, for stability, durability and deformation control. Cement-stabilization is one of the alternatives. An increase in strength and durability, reduction in deformability are the main aims of this method. Conventional cement-stabilization methods are used mainly for surface treatment. However, the use of cement has recently been extended to a greater depth in which cement columns were installed to act as a type of soil reinforcement (deep cement–soil mixing and cement jet grouting). In situ engineering properties of these silty–clayey soils are often variable and difficult to predict. For this reason cement-stabilization methods have a basic target to control the aforementioned engineering properties of these clays so that the properties of a silty–clayey soil become more like the properties of a soft rock such as clayey shale or lightly cemented sandstone. So cement-stabilization of these soils is essential to control their engineering properties and to predict their engineering behaviour for construction. In an effort to predict, classify and study the suitability of silty–clayey soils for cement-stabilization both slaking and unconfined compressive strength tests were carried out on clayey–sand mixtures consisted of two types of clays, kaolin and bentonite. Finally diagrams were prepared to study the variation of slaking and strength due to compaction, curing time and cement percentage and also to predict areas of efficient cement-stabilization.     

关于国土资源数据共享分类的思考

数据共享分类是制定数据共享政策和数据资源开发利用规划的一项基础性工作。本文 提出国土资源数据共享分类的意义、原则和方法,探讨建立以数据共享分类为核心的 国土资源数据分类体系,以期为全面开展国土资源数据共享分类提供参考。     

航磁异常的几种计算机分类方法

目前,应用计算机对航磁异常进行分类存在很大局限性。为克服这些局限性,将航磁异常分类的结果从定性水平提升到定量水平,这里应用三种分类方法在计算机上对航磁异常进行分类。经实例检验,分类结果令人满意,有效地改进和实现了用于航磁异常分类的定量方法。     

基于小波变换系数自适应阈值法在语音去噪中的应用

在软阈值去噪算法基础上，根据小波变换后信号与噪音具有的奇异性，提出无偏风险自适应阈值估计算法，并应用于语音信号的去噪处理，实验结果表明该算法的最小均方误差低于其他的去噪算法。     

Landsat7 ETM＋影像的融合和自动分类研究

利用SFIM、MLT、HPF和修改的Brovey(MB)等遥感影像融合算法对Landsat 7 ETM 影像进行融合和自动分类研究，并就融合影像的光谱保真度、高频空间信息融人度和分类精度对这些方法进行评价。结果表明SFIM变换几乎完全保持了原始影像的光谱特点，并具有最高的平均分类精度；MB变换具有最高的高频空间信息融人度；MLT变换也具有较高的分类精度；只有HPF变换的各项指标都不突出。所有4种融合影像的分类精度都较原始影像的分类精度有明显的提高。这表明，源于同一传感器系统的不同分辨率影像的融合可以避免异源传感器融合影像所常见的各种参数、时相和配准误差，所以能够明显地提高影像的自动分类精度。