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61.
针对大样本集的训练问题和动态训练样本的模型更新问题,提出了动态最小二乘支持向量机学习算法.该算法充分利用已建好的模型,逐渐加入新样本,并可删除位于任何位置的非支持向量,避免了矩阵求逆运算,保证了算法的高效率.大坝变形及电离层延迟两个时间序列的预报实例表明,该算法具有计算时间短、预报精度高的特点. 相似文献
62.
深部矿产资源的勘查是战略性矿产资源勘查的一个重要方面。找矿实践证明,化探方法技术在矿产勘查乃至深部找矿中发挥了重要的、不可或缺的作用。找矿工作的不断深入和找矿难度的不断加大,促使化探方法技术不断的发展和完善,在传统方法技术的基础上,研发出了许多新的方法技术。本文从方法论和系统论的角度出发,对现有的找寻深部隐伏矿盲矿的有效化探方法技术进行了系统的归纳和总结,提出了立体地球化学勘查方法技术体系的概念,将立体地球化学勘查方法技术划分为地面地球化学测量方法技术和地下地球化学测量方法技术,建立了深部矿产资源立体地球化学勘查方法技术体系。不同的方法技术有不同的优势和不同的适用条件,实际工作中应当根据不同的勘查阶段,不同的勘查目的和不同的地质地球化学条件选择不同的立体方法技术组合才能发挥出最大效益,取得最大效果。 相似文献
63.
对高层、超高层建筑物进行实时,高精度的变形监测对提前预防安全隐患,保证人民生命财产安全具有重要意义。建筑物变形作为一种典型的随机性和微弱性过程,噪声等误差的存在会影响从中提取有用的变形信息。针对该问题,提出一种改进粒子群(Particle Swarm Optimization,PSO)算法优化支持向量机(Support Vector Machine,SVM)的噪声稳健建筑物变形监测方法,利用改进PSO算法的全局搜索能力对SVM的核参数进行优化,提升预测精度的同时增强算法的噪声稳健性。基于实测数据的试验结果表明,相对于传统交叉验证SVM和小波方法,所提方法可以获得更高的变形预测精度,并且在低信噪比条件下优势更加明显。 相似文献
64.
Laboratory experiments were carried out to acquire more insight and understanding of the phenomena associated with the in-situ arsenic remediation. Visualization techniques are the most informative for the detection of Fe(II) while flowing in soils. Green Rust (GR) was considered as representative of in-situ iron precipitates. In a visualization flat cell, the change in color of GR to orange, due to oxidation, was monitored by a digital camera and the images were analyzed giving the spatial and temporal distribution of Fe(II). Moreover, both oxygen and pH changes in time were recorded in two sections along the flow direction in the cell. The measured and calculated concentration profiles were compared and the actual reaction rates were predicted. The reaction rate constants measured in this study, under flowing conditions, are in a good agreement with the values obtained from batch experiments reported in the literature. 相似文献
65.
Engineering geological studies and tunnel support design at Sulakyurt dam site, Turkey 总被引:2,自引:0,他引:2
H. Basarir 《Engineering Geology》2006,86(4):225-237
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
66.
以沈阳市某深基坑支护及降水工程在密集建筑群中施工为例,介绍了该支护工程的设计与施工,阐述了该工程变形监测方法并对其结果进行了分析,总结了在沈阳地区密集建筑群中进行基坑开挖的设计与施工经验。 相似文献
67.
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69.
A decision support system (DSS) has been developed to assist expert and non-expert users in the evaluation and selection of
eco-engineering strategies for slope protection. This DSS combines a qualitative hazard assessment of erosion and mass movements
with a detailed catalogue of eco-engineering strategies for slope protection of which the suitability is evaluated in relation
to the data entered. The slope decision support system (SDSS) is a knowledge based DSS in which knowledge is stored in frames
containing rules that can evaluate the available information for a project, stored as project specific information (PSI) in
a data file. The advantages of such a system are that it accepts incomplete information and that the qualitative nature of
the information does not instil the user with a sense of unjustified exactitude. By its multidisciplinary and progressive
nature, the DSS will be of value during the initial stages of an eco-engineering project when data collection and the potential
of different eco-engineering strategies are considered. The accent of the output of the DSS is on the application of eco-engineering
strategies for slope protection as an environmentally-friendly solution aiding sustainable development. For its acceptance
within the engineering community, the DSS needs to prove its predictive capacity. Therefore, its performance has been benchmarked
against successful and unsuccessful cases of slope stabilisation using eco-engineering. The target audience and the areas
of application of this DSS are reviewed and the strategies for further development in this area suggested. 相似文献
70.