山东焦家金成矿带三维地质建模及成矿预测

以山东焦家金成矿带为研究对象,将焦家金矿带的二维地质资料有效整合,应用三维建模软件Surpac,首次建立了该矿区的三维数字矿山模型.以此模型为基础,以地质统计方法为手段,分析成矿规律,建立找矿模型.成矿预测中利用“立方体预测模型”找矿方法、找矿信息量法和证据权法来预测资源量,按照信息值的等级依次圈定了6个成矿靶区.用体积估计法和丰度值估计法2种完全不同的计算方法来预测资源量,2种方法得到的找矿靶区资源量均约为380 t,说明计算的结果具有一致性和稳定性.     

利用断层应力积累探讨大地震发生的地点——以日本2011年东北9级大地震为例

大地震在哪里发生是地震预报首先要解决的问题.利用反演GNSS观测数据得到的2011年日本东北9级大地震前7年(2004-2010年)断层上的应力变化,我们发现了这次地震断层的孕震区.为了进一步研究该孕震区的演化过程,本文继续反演这次大地震在1997-2003年间的断层应力变化过程.通过这两期的反演工作,我们看到,在这1...     

地震动力分析的经典方法与现代计算技术

回顾了体系地震动力分析的历史过程，并对地震动力分析的传统理论方法、近似方法和现代计算技术从新的角度加以阐述，同时给出体系地震动力分析的应用前景，以促进经典的传统理论方法、近似方法和现代计算技术的综合和在实际工程中的应用，形成系统而完整的地震动力分析体系。     

辽宁水泉金矿成矿规律及矿山远景评价

用综合信息矿产资源定量预测的理论和方法，系统研究了辽宁水泉金矿成矿规律及控矿因素，特别是对控矿构造特征作了深入的研究，并建立了研究区的综合信息找矿模型。对水泉金矿的区域成矿远景和深部成矿远景进行了综合预测。     

矿井涌水量预测的比拟法计算公式待定系数讨论

以典型矿山多年实际的开采及排水序列资料为基础、相关学科理论为指导,通过对开采及排水资料的"二次开发",探讨了不同水文地质类型矿床的矿井涌水量预测比拟法计算公式中待定系数的特点,以及随开采面积(F)和开采疏干降深(S)的变化趋势和规律。研究结果表明:参数"m"、"n"是随开采疏干降深(S)和开采面积(F)增加而加大的变量;不同类型矿床中参数n值均大于m值;岩溶水充水矿床中参数"m"、"n"相对稳定,而基岩裂隙水充水矿床具有明显的分段性特征。指出了单纯"面积比拟法"、"降深比拟法"对矿井涌水量预测的不合理性,以及在参数"m"、"n"取值中加强水文地质勘查资料综合研究的重要性。     

Land use/land cover change detection and prediction in the north-western coastal desert of Egypt using Markov-CA

Detecting land-use change has become of concern to environmentalists, conservationists and land use planners due to its impact on natural ecosystems. We studied land use/land cover (LULC) changes in part of the northwestern desert of Egypt and used the Markov-CA integrated approach to predict future changes. We mapped the LULC distribution of the desert landscape for 1988, 1999, and 2011. Landsat Thematic Mapper 5 data and ancillary data were classified using the random forests approach. The technique produced LULC maps with an overall accuracy of more than 90%. Analysis of LULC classes from the three dates revealed that the study area was subjected to three different stages of modification, each dominated by different land uses. The use of a spatially explicit land use change modeling approach, such as Markov-CA approach, provides ways for projecting different future scenarios. Markov-CA was used to predict land use change in 2011 and project changes in 2023 by extrapolating current trends. The technique was successful in predicting LULC distribution in 2011 and the results were comparable to the actual LULC for 2011. The projected LULC for 2023 revealed more urbanization of the landscape with potential expansion in the croplands westward and northward, an increase in quarries, and growth in residential centers. The outcomes can help management activities directed toward protection of wildlife in the area. The study can also be used as a guide to other studies aiming at projecting changes in arid areas experiencing similar land use changes.     

样本输入方式对极端学习机预报日长变化的影响

针对极端学习机(Extreme Learning Machine,ELM)用于日长(Length-Of-Day,LOD)变化预报过程中,样本输入方式对预报结果的影响进行了研究。采用跨度、连续和迭代3种样本输入方式对日长变化进行预报。结果表明,不同的样本输入方式对预报结果有很大影响,样本按跨度输入的预报精度最低;样本采用连续输入方式在短期和中长期预报中预报精度较高,但计算速度较慢,较适合中长期预报;样本按迭代输入方式的短期预报精度稍优于连续输入方式,而中长期预报精度则不如连续输入方式,但具有较高的预报效率。这对于日长变化的实时快速预报有着较高的现实意义。     

Higher Dimensional FRW Cosmological Models in Self-Creation Theory

The field equations of Barber's (1982) second self-creation theory of gravitation are solved for 5D Friedmann-Robertson-Walker space time using perfect fluid energy momentum tensor. By assuming an equation of state p= ε ρ, (0 ≤ ε ≤ 1), the solutions of the field equations, in different scenarios, in Barber's second self-creation theory are presented and discussed. Some properties of these models are also discussed.     

Geoeffective Analysis of CMEs Under Current Sheet Magnetic Coordinates

Using 100 CME–ICME events during 1997.01–2002.11, based on the eruptive source locations of CMEs and solar magnetic field observations at the photosphere, a current sheet magnetic coordinate (CMC) system is established in order to statistically study the characteristics of the CME–ICME events and the corresponding geomagnetic storm intensity. The transit times of CMEs from the Sun to the Earth are also investigated, by taking into account of the angle between the CME eruption normal (defined as the vector from the Sun center to the CME eruption source) and the Sun-Earth line. Our preliminary conclusions are: 1. The distribution of the CME sources in our CMC system is obviously different from that in the ordinary heliographic coordinate system. The sources of CMEs are mainly centralized near the heliospheric current sheet (HCS), and the number of events decreases with the increment of the angular distance from the CME source to the HCS on the solar surface; 2. A large portion of the total events belong to the same–side events (referring to the CME source located on the same side of the HCS as the Earth), while only a small portion belong to the opposite–side events (the CME source located on the opposite side of the HCS as the Earth). 3. The intense geomagnetic storms are usually induced by the same–side events, while the opposite side events are commonly associated with relatively weak geomagnetic storms; 4. The angle between the CME normal and the Sun–Earth line is used to estimate the transit time of the CME in order to reflect the influence of propagation characteristic of the CME along the Sun–Earth direction. With our new prediction method in context of the CMC coordinate, the averaged absolute error for these 100 events is 10.33 hours and the resulting relative error is not larger than 30% for 91% of all the events.     

Bias and uncertainty in regression-calibrated models of groundwater flow in heterogeneous media

Groundwater models need to account for detailed but generally unknown spatial variability (heterogeneity) of the hydrogeologic model inputs. To address this problem we replace the large, m-dimensional stochastic vector β that reflects both small and large scales of heterogeneity in the inputs by a lumped or smoothed m-dimensional approximation γθ_∗, where γ is an interpolation matrix and θ_∗ is a stochastic vector of parameters. Vector θ_∗ has small enough dimension to allow its estimation with the available data. The consequence of the replacement is that model function f(γθ_∗) written in terms of the approximate inputs is in error with respect to the same model function written in terms of β, f(β), which is assumed to be nearly exact. The difference f(β) − f(γθ_∗), termed model error, is spatially correlated, generates prediction biases, and causes standard confidence and prediction intervals to be too small. Model error is accounted for in the weighted nonlinear regression methodology developed to estimate θ_∗ and assess model uncertainties by incorporating the second-moment matrix of the model errors into the weight matrix. Techniques developed by statisticians to analyze classical nonlinear regression methods are extended to analyze the revised method. The analysis develops analytical expressions for bias terms reflecting the interaction of model nonlinearity and model error, for correction factors needed to adjust the sizes of confidence and prediction intervals for this interaction, and for correction factors needed to adjust the sizes of confidence and prediction intervals for possible use of a diagonal weight matrix in place of the correct one. If terms expressing the degree of intrinsic nonlinearity for f(β) and f(γθ_∗) are small, then most of the biases are small and the correction factors are reduced in magnitude. Biases, correction factors, and confidence and prediction intervals were obtained for a test problem for which model error is large to test robustness of the methodology. Numerical results conform with the theoretical analysis.