Precipitation-runoff simulation for a Himalayan River Basin, India using artificial neural network algorithms

In the Himalayan regions, precipitation-runoff relationships are amongst the most complex hydrological phenomena, due to varying topography and basin characteristics. In this study, different artificial neural networks (ANNs) algorithms were used to simulate daily runoff at three discharge measuring sites in the Himalayan Kosi River Basin, India, using various combinations of precipitation-runoff data as input variables. The data used for this study was collected for the monsoon period (June to October) during the years of 2005 to 2009. ANNs were trained using different training algorithms, learning rates, length of data and number of hidden neurons. A comprehensive multi-criteria validation test for precipitation-runoff modeling has been undertaken to evaluate model performance and test its validity for generating scenarios. Global statistics have demonstrated that the multilayer perceptron with three hidden layers (MLP-3) is the best ANN for basin comparisons with other MLP networks and Radial Basis Functions (RBF). Furthermore, non-parametric tests also illustrate that the MLP-3 network is the best network to reproduce the mean and variance of observed runoff. The performance of ANNs was demonstrated for flows during the monsoon season, having different soil moisture conditions during period from June to October.     

Cumulative gain and lift charts for model performance assessment in mineral potential mapping

Model performance assessment is a key procedure for mineral potential mapping, but the corresponding research achievements are seldom reported in literature.Cumulative gain and lift charts are well known in the data mining community specialized in marketing and sales applications and widely used in customer churn prediction for model performance assessment.In this paper, they are introduced into the field of mineral potential mapping for model performance assessment.These two charts can be viewed as a graphic representation of the advantage of using a predictive model to choose mineral targets.A cumulative gain curve can represent how much a predictive model is superior to a random guess in mineral target prediction.A lift chart can express how much more likely the mineral targets predicted by a model are deposit-bearing ones than those by a random selection.As an illustration, the cumulative gain and lift charts are applied to measure the performance of weights of evidence, logistic regression, restricted Boltzmann machine, and multilayer perceptron in mineral potential mapping in the Altay district in northern Xinjiang in China.The results show that the cumulative gain and lift charts can visually reveal that the first three models perform well while the last one performs poorly.Thus, the cumulative gain and lift charts can serve as a graphic tool for model performance assessment in mineral potential mapping.     

云南东川铜矿床流体演化与成矿机制研究

东川铜矿床是我国重要的沉积岩容矿的层状铜矿床(SSC),具有显著的多层位成矿特征和典型的铜硫化物分带。本研究以不同层位铜矿体的流体包裹体为研究对象,通过岩相学观察、显微测温和激光拉曼成分分析,发现东川群多层位铜矿体存在浅色和深色包裹体2种类型:浅色包裹体成分以H₂O为主,含丰富的石盐子晶和少量钾盐、硬石膏子晶,代表了氧化型含矿卤水,具中低温(140~300 ℃)、中高盐度(12%~44%)的特征,属于Na ⁺、K ⁺、Ca ²⁺-Cl ^-(SO₄ ^2-)型盆地卤水,主要来源于海相蒸发岩的溶解和层间建造水;深色的含有机质包裹体代表了还原型流体,来源于黑山组碳质板岩和落雪组中的藻类生物分解。东川铜矿床以落雪组的含叠层石砂质白云岩作为主要沉淀系统,黑山组碳质板岩为隔挡层,形成一个流体封闭的物理化学圈闭,氧化含矿卤水通过供给系统运移到具还原性质的沉淀系统中,与还原型富硫流体和含有机质的地层发生混合反应,形成多层位的层状铜矿体和层控脉状铜矿体。     

海域使用权立体分层确权及管理配套制度探讨

由于社会经济的不断发展和科技的快速进步,我国对海域空间资源的开发利用已从二维平面转向三维立体空间开发,但随之也对我国海域空间范围界定和权属管理提出了更高的要求。文章从海域立体空间分层特性出发,对我国海域使用权立体分层确权的内涵、基本原则、考虑因素进行了深入剖析,并对我国海域三维立体开发利用中面临的困境和管理配套制度的设计进行了综合探讨。研究结果表明：海域空间可以分为水面上方、水面、水体、海床和底土5个部分,海域使用权立体分层确权则是在同一海域多层次利用中,对基于特定功能用途所占用的特定海域空间开展使用权确权的过程,在海域使用权管理的过程中,必须构建和完善海域空间三维产权法律制度体系,以确保海域使用权立体分层确权的实施。     

多阶多层复杂边坡稳定性的通用上限方法

极限分析上限方法在边坡稳定性评价中受到了广泛关注,但当前所取得的解析成果尚不能直接应用于解决任意多土层分布、多台阶的广义复杂层状边坡。基于组合对数螺线的旋转破坏机制,推导了具有任意坡面几何特征、任意多土层（含非水平土/岩层）边坡的外功率统一积分表达式及相应的虚功率方程,提出了多阶多层复杂边坡稳定性的通用极限分析上限方法;为克服积分式的复杂解析计算,引入了数值积分技术。在此基础上,结合最优化方法和强度折减技术,优化求解了复杂边坡的全局稳定性安全系数及相应的临界滑动面。通过多个典型算例的验证与对比分析,表明该方法具有较高的精度和广泛适用性。最后,针对典型多阶多层边坡实例,开展了上限法的深度拓展与应用研究,其结果为广义复杂层状边坡的稳定性评价提供了新思路。     

基于多层反卷积网络的SAR图像分类

针对传统特征提取方法不能提取目标高层结构特征的问题,提出了一种基于软概率的池化方法,结合多层反卷积网络,学习目标的高层结构特征,并将其用于合成孔径雷达(SAR)图像分类。首先对SAR图像进行子块划分,然后对每个子块进行基于多层反卷积网络的特征编码,学习出不同层次上的图像特征,最后将该特征用于支持向量机(SVM)分类器,实现SAR图像的分类。在国内首批SAR数据上的实验表明,该算法获得了较高的分类准确率。     

三维多层介质重力-地震同步联合反演

联合反演是地球物理勘探的重要解释手段,能够提高模型参数的反演精度.本文在归纳和分析重力与地震资料联合反演的研究和应用现状的基础上,利用三维多层介质模型的地震走时和重力正演公式,推导了地震走时和重力异常对界面深度的雅可比矩阵,实现了三维重力-地震同步联合反演界面成像.最后进行了数值理论模型模拟和实例计算,结果表明地震走时和重力同步联合反演很好的重建了三维多层介质界面.     

分层抽取法在泥沙沉积过程中的应用研究

悬浮泥沙到沉积土的形成过程非常复杂,涉及到泥沙的沉降和土的自重固结。物理模型试验需要实测含水率、密度、颗粒分布、超孔隙水应力和总应力,但目前尚无简单可行的方法。提出了一种改进的室内试验方法,通过与国内外现有试验方法相对比,改进后的方法不仅可以得到泥沙在沉积过程中的泥面下沉变化、含水率（密度）分布、超孔压消散剖面,而且还能得到沉积物在不同高度和时间的颗粒分布变化等性质。通过多个试验实测及一致性测试表明,实测数据合理、可信,一致性检验误差较小,验证了此方法的可行性。     

多层叠置含煤层气系统不同排采制度下的排采效应

在多煤层发育地区,各煤层组之间发育低渗透岩层,使得上下煤组之间形成独立的多层叠置含煤层气系统。根据相对独立含气系统理论对西山煤田南部赤峪地区的多煤层进行了含气系统的划分,并对储层压力、临界解吸压力等参数进行了分析,在此基础上采用COMET3数值模拟软件进行了单层排采、合层排采和递进排采分析。模拟结果显示：单层排采产量低,经济可采时间短,且成本较高;合层排采比单层排采产量高,经济可采时间长,但各含气系统之间由于相互干扰,贡献不一,使资源浪费;递进排采产气量和稳产时间均优于前两者。可根据产气压力来确定多层叠置含煤层气系统排采次序,首先排采产气压力最高的含气系统,当压力降至压力低的系统时再合排。