基于Weka的地震数据挖掘系统的设计与实现

基于开源的数据挖掘系统Weka,使用Java语言及面向对象的思想,设计并实现了地震数据挖掘系统。根据地震数据资料的特点,将数据挖掘的核心技术（聚类分析、关联规则分析等）引入到该系统中,其中聚类分析选用DBSCAN作为核心算法,关联规则分析选用Apriori作为核心算法。用户使用该系统只需在交互界面选择相关参数,即可实现调用数据挖掘算法来分析地震数据,发现探索其隐含规律。     

空间同位模式支持下城市服务业关联发现及特征分析

空间同位模式分析是数据挖掘中一种常见的方法,可有效挖掘城市设施在空间位置上的关联特征,进而发现城市设施的分布规律.本文基于POI数据同位模式挖掘用来获取城市服务业空间关联结构:首先,通过邻近实例获取、同位候选模式存储与筛选,得到城市服务业二阶同位模式;然后,据此构造产业空间关联图,得到产业间的关联结构;最后,分别构造了...     

水牛蹄型深海集矿机履齿设计及牵引性能研究

作为深海采矿系统的重要组成部分,深海集矿机的技术研究和开发一直是许多国家的难题。为了提高深海集矿机在稀软沉积物上的牵引性能,基于水牛蹄的曲面结构特征和特殊几何结构,设计了一款仿水牛蹄蹄型履齿。以该款履齿的结构参数为研究对象,通过对朗肯被动土压力理论的优化,得到了仿水牛蹄蹄型履齿的牵引力解析解,建立了对应的履齿仿生参数对履齿牵引力的影响公式。结合正交试验方法进行了不同形式履齿在沉积物上运动的单、多履齿剪切试验,将仿水牛蹄蹄型履齿与直型履齿、仿水牛蹄轮廓履齿（另一种仿生履齿）进行对比试验,并通过模型车试验验证了该款履齿的可行性。结果表明：3种履齿中,仿水牛蹄蹄型履齿提供的最大牵引力最高。研究可为进一步优化仿水牛蹄蹄型履齿结构参数和提高深海稀软底质机械的牵引性能提供参考依据。     

徐州矿区地裂缝成因机制的探讨

调查了徐州矿区几类非采矿沉陷造成的地裂缝的形态和环境,认为因构造、采矿、不均匀沉降产生的隐伏张裂隙是地裂缝的基础,干旱和超采浅层地下水使第四系浅部失水收缩激活和扩大了隐伏张裂隙。大雨后地裂缝显现,雨水沿裂隙面下渗时,发生潜蚀、刷大、贯通而造成塌陷。     

综放开采顶煤裂隙及其对渗透性研究的意义

在对综放工作面的煤样进行微观研究基础上,首次运用多重分形理论对顶煤裂隙的不均匀性和各向异性进行了定量表征,并将顶煤裂隙不均匀系数运用于渗透系数研究中,计算结果与实测基本吻合,表明运用多重分形方法,可为研究顶煤节理裂隙及其渗透性研究提供一个新的方法。     

西南煤系地层山区采动型崩滑灾害研究关键问题

文章在分析采矿型崩滑灾害发育特征的基础上,得出西南煤系地层山区地下采动型崩滑灾害常发生在层状碳酸盐岩与碎屑岩地层组成的褶皱翼部和核部的陡崖带上,与地形地貌、地层结构与地下采矿工程活动等因素关系密切,并指出薄矿层开采诱发大型山体崩滑灾害的具体过程：①采空后覆岩顶板塌落—覆岩顶板离层,采空区上覆岩层内部及层间自下而上应力传递;②地下水运移通道形成,并加快更大范围岩体结构破坏及扩展,加速了岩体结构面的松动与破坏;③上覆岩层不均匀沉降导致坡脚压裂,山体大型岩体结构面逐渐拉剪或压剪变形扩展,最终山体发生累积损伤与大规模崩滑灾害。此外,传统经验公式的计算方法对此类采矿型崩滑灾害已不适用,建议开展西南煤系地层山区地质结构与地下采动诱发崩滑灾害的相互作用关系、薄矿层采空区上部山体累积断裂损伤—岩体松动、裂隙扩展-岩溶管道流、裂隙流变化的链式响应机制、地下采动型崩滑灾害评价方法等关键科学问题的研究,以推动采矿型地质灾害防灾减灾工作的发展。     

缓倾斜煤层走向长壁式工作面地表沉陷盆地模型

为准确描述地表沉陷盆地分布形态,基于幂指数函数模型,结合缓倾斜煤层走向长壁式工作面地表沉陷盆地的特征,采用理论分析与数值模拟相结合的方法,建立适用于缓倾斜煤层走向长壁式工作面的沉陷盆地模型,分析模型参数的影响因素及参数的变化规律,并验证模型的适用性和预计精度。研究表明：模型参数n反映下沉盆地底部范围大小,主要与采动程度有关,取值范围为1~3,其取值精度取决于观测点个数;参数k反映下沉盆地边缘的收敛速度和下沉影响范围,主要与采煤方法、顶板管理方法及松散层厚度有关,其值可通过地表最大下沉值或煤厚进行确定;在对常村煤矿地表沉陷进行预计时,预计值与实测值的差值平方和为3.08×10⁶,中误差为267.59 mm,为最大下沉值的6.47%。研究缓倾斜煤层走向长壁式工作面地表沉陷盆地模型旨在对常村煤矿地表沉陷的预测和预防工作提供理论基础。     

Soil property variation mapping through data mining of soil category maps

Spatial information on soil properties is an important input to hydrological models. In current hydrological modelling practices, soil property information is often derived from soil category maps by the linking method in which a representative soil property value is linked to each soil polygon. Limited by the area‐class nature of soil category maps, the derived soil property variation is discontinuous and less detailed than high resolution digital terrain or remote sensing data. This research proposed dmSoil, a data‐mining‐based approach to derive continuous and spatially detailed soil property information from soil category maps. First, the soil–environment relationships are extracted through data mining of a soil map. The similarity of the soil at each location to different soil types in the soil map is then estimated using the mined relationships. Prediction of soil property values at each location is made by combining the similarities of the soil at that location to different soil types and the representative soil property values of these soil types. The new approach was applied in the Raffelson Watershed and Pleasant Valley in the Driftless Area of Wisconsin, United States to map soil A horizon texture (in both areas) and depth to soil C horizon (in Pleasant Valley). The property maps from the dmSoil approach capture the spatial gradation and details of soil properties better than those from the linking method. The new approach also shows consistent accuracy improvement at validation points. In addition to the improved performances, the inputs for the dmSoil approach are easy to prepare, and the approach itself is simple to deploy. It provides an effective way to derive better soil property information from soil category maps for hydrological modelling. Copyright © 2014 John Wiley & Sons, Ltd.     

Water mining from the deep critical zone by apple trees growing on loess

There have been significant recent advances in understanding the ecohydrology of deep soil. However, the links between root development and water usage in the deep critical zone remains poorly understood. To clarify the interaction between water use and root development in deep soil, we investigated soil water and root profiles beyond maximum rooting depth in five apple orchards planted on farmland with stand ages of 8, 11, 15, 18, and 22 years in a subhumid region on the Chinese Loess Plateau. Apple trees rooted progressively deeper for water with increasing stand age and reached 23.2 ± 0.8 m for the 22‐year‐old trees. Soil water deficit in deep soil increased with tree age and was 1,530 ± 43 mm for a stand age of 22 years. Measured root deepening rate was far great than the reported pore water velocity, which demonstrated that trees are mining resident old water. The deficits are not replenished during the life‐span of the orchard, showing a one‐way mining of the critical zone water. The one‐way root water mining may have changed the fine root profile from an exponential pattern in the 8‐year‐old orchard to a relative uniform distribution in older orchards. Our findings enhance our understanding of water‐root interaction in deep soil and reveal the unintended consequences of critical zone dewatering during the lifespan of apple trees.     

Erodibility of low‐compaction steep‐sloped reclaimed surface mine lands in the southern Appalachian region,USA

The use of loose spoils on steep slopes for surface coal mining reclamation sites has been promoted by the US Department of Interior, Office of Surface Mining for the establishment of native forest, as prescribed by the Forest Reclamation Approach (FRA). Although low‐compaction spoils improve tree survival and growth, erodibility on steep slopes was suspected to increase. This study quantified a combined K_C factor (combining the effects of the soil erodibility K factor and cover management C) for low compaction, steep‐sloped (>20°) reclaimed mine lands in the Appalachian region, USA. The combined K_C factor was used because standard Unit Plot conditions required to separate these factors, per Revised Universal Soil Loss Equation (RUSLE) experimental protocols, were not followed explicitly. Three active coal mining sites in the Appalachian region of East Tennessee, each containing four replicate field plots, were monitored for rainfall and sediment yields during a 14‐month period beginning June 2009. Average cumulative erosivity for the study sites during the monitoring period was measured as 5248.9 MJ·mm·ha^?1·h^?1. The K_C ranged between 0.001 and 0.05 t·ha·h·ha^?1·MJ^?1·mm^?1, with the highest values occurring immediately following reclamation site construction as rills developed (June – August 2009). The K_C for two study sites with about an 18–20 mm spoil D₈₄ were above 0.01 t·ha·h·ha^?1·MJ^?1·mm^?1 during rill development, and below 0.003 t·ha·h·ha^?1·MJ^?1·mm^?1 after August 2009 for the post‐rill development period. The K_C values for one site with a 40 mm spoil D₈₄ were never above 0.008 t·ha·h·ha^?1·MJ^?1·mm^?1 and also on average were lower, being more similar to the other two sites after the rill development period. Based on an initial K_C factor (K_e) measured during the first few storm events, the average C factor (C_e) was estimated as 0.58 for the rill development period and 0.13 for the post‐rill development period. It appears that larger size fractions of spoils influence K_C and C_e factors on low‐compaction steep slopes reclamation sites. Copyright © 2013 John Wiley & Sons, Ltd.