基于邻域粗糙集和支持向量机的固结系数预测     

尹超  周爱红  袁颖  王帅伟 《吉林大学学报(地球科学版)》2019,49(3):746-754

采用邻域粗糙集和支持向量机建立滹沱河某地区软土固结系数的预测模型。基于自行改装的渗透固结仪,利用公式法确定不同压力下的固结系数。通过室内试验确定土体的指标参数,采用邻域粗糙集对该指标参数进行属性约简,将约简后的指标参数作为影响因素,分别建立支持向量机和神经网络的固结系数预测模型,预测未知样本的固结系数,并与实测值进行对比。结果表明:公式法可以准确客观地确定固结系数;支持向量机和BP神经网络建立的该地区软土固结系数预测模型均可以预测区域内未知点的固结系数,且支持向量机方法的预测精度比神经网络方法的预测精度提高了约10%。本文提出的方法直接从实验数据出发,通过易获取的影响因素建立特定地区固结系数预测模型,并可预测该区域其余未知点的固结系数。  相似文献   

地理作用和集聚演化：基于数据挖掘的分析   总被引：1，自引：0，他引：1  

葛莹  吴野 《地理科学进展》2009,28(6):855-862

经济集聚是工业社会中一种普遍存在的地理现象。它可以发生在不同的地理层面上,具有多种空间组织结构。在回答地理是否会影响集聚演化的问题上存在着两种不同的观点。其一是认为良好的地理环境将有助于经济集聚的产生,并且地理作用在其发展过程中持续存在;其二是认为地理仅是集聚形成的一个触发因子,其发展可以依赖纯经济因素而不是比较优势。本文运用数据挖掘技术,将演化时段分成集聚形成和集聚发展二个阶段,从另一个角度详细分析这两种观点。研究结论表明,集聚的形成受到自然地理要素的影响比经济地理要素要大。但经济地理要素对集聚增长具有显著的作用,经济因素和交通因素是集聚规模增加的关键所在,而自然地理因素作用被削弱了。  相似文献   

Probabilistic reservoir operation using Bayesian stochastic model and support vector machine   总被引：3，自引：0，他引：3  

Mohammad Karamouz  Azadeh Ahmadi  Ali Moridi   《Advances in water resources》2009,32(11):1588-1600

Available water resources are often not sufficient or too polluted to satisfy the needs of all water users. Therefore, allocating water to meet water demands with better quality is a major challenge in reservoir operation. In this paper, a methodology to develop operating strategies for water release from a reservoir with acceptable quality and quantity is presented. The proposed model includes a genetic algorithm (GA)-based optimization model linked with a reservoir water quality simulation model. The objective function of the optimization model is based on the Nash bargaining theory to maximize the reliability of supplying the downstream demands with acceptable quality, maintaining a high reservoir storage level, and preventing quality degradation of the reservoir. In order to reduce the run time of the GA-based optimization model, the main optimization model is divided into a stochastic and a deterministic optimization model for reservoir operation considering water quality issues.The operating policies resulted from the reservoir operation model with the water quantity objective are used to determine the released water ranges (permissible lower and upper bounds of release policies) during the planning horizon. Then, certain values of release and the optimal releases from each reservoir outlet are determined utilizing the optimization model with water quality objectives. The support vector machine (SVM) model is used to generate the operating rules for the selective withdrawal from the reservoir for real-time operation. The results show that the SVM model can be effectively used in determining water release from the reservoir. Finally, the copula function was used to estimate the joint probability of supplying the water demand with desirable quality as an evaluation index of the system reliability. The proposed method was applied to the Satarkhan reservoir in the north-western part of Iran. The results of the proposed models are compared with the alternative models. The results show that the proposed models could be used as effective tools in reservoir operation.  相似文献   

复杂应力下充填体破坏能耗试验研究   总被引：3，自引：0，他引：3  

邓代强  高永涛  吴顺川  余伟健 《岩土力学》2010,31(3):737-742

应用先进的MTS和INSTRON刚性伺服试验机对不同灰砂比的充填体进行了常规三轴、无侧限单轴动态、静态抗压强度试验,测得了各种相关力学参数,得到了对应的荷载-位移和应力-应变全曲线,根据所得试验力学参数和压缩试验的性质,将单个试件、单位体积、单位质量的破坏能耗作为考查指标,计算了三轴和单轴抗压动态、静态加载方式下的破坏能耗,计算过程中消除了负位移产生的不利影响,通过统计回归建立和分析了围压与能耗的函数关系和不同情况下破坏能耗的变化及规律,对矿山顺利回采矿柱、维护采场及巷道顶板稳定、控制地压、防止地表塌陷、环境保护等具有现实意义。  相似文献   

Potential of support vector regression for prediction of monthly streamflow using endogenous property   总被引：2，自引：0，他引：2  

Rajib Maity  Parag P. Bhagwat  Ashish Bhatnagar 《水文研究》2010,24(7):917-923

In the recent past, a variety of statistical and other modelling approaches have been developed to capture the properties of hydrological time series for their reliable prediction. However, the extent of complexity hinders the applicability of such traditional models in many cases. Kernel‐based machine learning approaches have been found to be more popular due to their inherent advantages over traditional modelling techniques including artificial neural networks(ANNs ). In this paper, a kernel‐based learning approach is investigated for its suitability to capture the monthly variation of streamflow time series. Its performance is compared with that of the traditional approaches. Support vector machines (SVMs) are one such kernel‐based algorithm that has given promising results in hydrology and associated areas. In this paper, the application of SVMs to regression problems, known as support vector regression (SVR), is presented to predict the monthly streamflow of the Mahanadi River in the state of Orissa, India. The results obtained are compared against the results derived from the traditional Box–Jenkins approach. While the correlation coefficient between the observed and predicted streamflows was found to be 0·77 in case of SVR, the same for different auto‐regressive integrated moving average (ARIMA) models ranges between 0·67 and 0·69. The superiority of SVR as compared to traditional Box‐Jenkins approach is also explained through the feature space representation. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

软岩隧道围岩加固方法优化对比试验研究与分析     

李丹  白世伟  陈陆望  陈浩  赵瑜 《岩土力学》2010,31(Z1):145-149

为解决软岩隧道工程的支护优化设计问题,研制出力学曲线与原岩相似的模型材料,形成软岩工程常用的支护设计方法对应的物理模型,即锚杆支护、锚喷支护、锚杆加长的锚喷支护,加上毛洞模型作为参考模型,4种平面模型形成三维模型后,置入大型真三轴模型试验机,在模型边界相同的条件下对软岩隧道的支护方法进行研究。试验结果表明：不同的支护方式具有不同的超载能力和不同的破坏特点;该相似模型材料对软岩大变形特点具有良好的适用性。试验还为软岩隧道支护设计提供了可靠的研究基础。  相似文献   

遥感植物地球化学方法的研究进展          下载免费PDF全文

崔世超  周可法  赵杰 《地质找矿论丛》2017,32(3):440-446

近些年来随着遥感技术的不断发展,在植被覆盖区的金属矿床的探查中,遥感植物地球化学方法得到了越来越广泛的应用。文章从理论、技术和应用三个方面对遥感植物地球化学方法的发展进行阐述,并指出目前存在的问题。其中使用定量化的手段提取植物地球化学信息是未来的必由之路。然而在定量化的过程中,光谱尺度效应和空间尺度效应是两个重要的影响模型精度的因素。针对这个问题,文章提出两种解决方案来减小光谱尺度效应的影响,然而这两种方法的可操作性以及可靠性还需要进一步探讨。最后,文章对遥感植物地球化学方法的发展前景进行阐述,并指出在以后定量模型的建立中可以引入支持向量机、投影追踪等机器学习的方法。  相似文献   

A dredged material solidification treatment for fill soils in East China: A case history     

Yinghao Huang  Chan Dong  Chunlei Zhang  Kai Xu 《Marine Georesources & Geotechnology》2017,35(6):865-872

Large amounts of sediments are dredged annually from Chinese oceans. Dredged materials (DMs) possess poor geotechnical properties and are normally treated as waste. This paper presents the first large-scale engineering application of DM solidification treatment in China. The technique has been used to treat approximately 1.8?×?10⁶?m³ of DM from Taihu Lake to produce fill soils. Portland cement was chosen as the solidification material, the amount of which is confirmed through indoor unconfined compressive strength (UCS) tests. Special solidification machines process DM at 120?m³/hours. Field-based DM solidification engineering began in September 2006. Curing specimens were examined over 28 days. Results show that both UCS and failure strain of solidified DM could meet fill soil requirements. Bearing capacity was also assessed with a cone penetrometer test. Samples were examined after 2 years (after project completion), and the mean UCS of the specimens was 237.2?kPa, which completely satisfied the engineering request. Wuxi Taihu City Science and Technology Industrial Park has now been established on top of the solidified DM storage yard. The successful engineering of such facilities results in economic and environmental benefits; thus, engineering applications of DM solidification treatment are widely promoted in China.  相似文献   

基于灰色关联和相关向量机的隧道地表沉降预测     

张立亭  徐志宽  罗亦泳 《大地测量与地球动力学》2017,37(10):1033-1037

基于灰色关联算法确定与地表沉降有直接重要关联的主要影响因子,构建高斯核函数和多项式核函数的加权核函数,利用遗传算法优化模型参数,建立相关向量机地表沉降预测模型。实验结果表明,灰色关联算法能定量地反映系统影响因子与地表沉降变化的关联程度,有效处理不是完全明确的灰色系统信息;加权核函数的合理组合可较好地通过低维空间线性不可分映射变换到高维特征空间线性可分;遗传算法具有计算过程简单和自适应迭代寻优特点;相关向量机模型可极大地减少核函数的计算量,计算过程和结果均具有概率解释。该模型预测结果的多项精度指标值均优于BP神经网络和GR-SVM方法。  相似文献   

基于随机森林算法的多维情境特征活动识别     

刘克强  汪云甲  陈锐志  褚天行 《测绘通报》2017,(7):29

利用智能手机传感器可感知时间、空间、时空和用户等多维情境的特征,可识别用户活动,但原框架模型中仅利用了单一分类器中的朴素贝叶斯算法,存在分类精度效果受限的问题。本文利用集成分类器中的随机森林算法对原有框架中的单一分类器进行了改进。在获取的3个数据集上的十倍交叉验证结果表明,加权平均F1量测值均有较大提高,表明利用随机森林算法在分类精度效果上有所提升;但由于集成算法结构相对复杂,其学习效率相对较低。此外,随机森林算法的分类混淆矩阵表明,导致识别误差的因素主要为活动的定义与室内定位精度。  相似文献