基于前传式网络逼近的太平洋副热带高压活动的诊断预测

基于前传式神经网络BP算法(BackpropagationNeuralNetwork)和回归模型,探讨了西太平洋副高面积指数同赤道东太平洋海温及赤道纬向风之间非线性分类和映射逼近的建模方法和效果比较.结果表明,前传式网络,特别是回归网络预报模型具有较好拟合精度和预报效果及比较实用的预报时效.     

浅水湖泊水生植被遥感监测研究进展

在浅水湖泊中,水生植物具有净化水质、抑制藻类、提供鱼类食物和栖息环境等生态功能,同时,其过度扩张也会加速湖泊淤浅和沼泽化、引起湖泊二次污染等环境负效应.实时动态地掌握湖泊水生植被类群和种群的空间分布及其面积、生物量等指标信息,对湖泊生态修复和评估、水生植被恢复和管理等具有重要现实意义.遥感技术的大面积、实时、动态等特点...     

地理空间要素与贫困分布的关系研究——以赫章县为例

本文以赫章县为例,以乡镇为研究单元,从地形地貌、土地资源、交通条件等方面构建地理空间要素评价指标。并利用地理探测器、地理加权回归模型等方法,从空间的视角科学分析地理空间要素对贫困化空间分布的影响,揭示了贫困程度与资源环境的空间分布规律,为实现因地制宜、精准脱贫,以及巩固脱贫摘帽成果提供了决策参考。     

西藏纳木错晚更新世以来湖面变化和湖相沉积中粘土矿物显示的环境信息

通过对西藏海拔最高、面积最大湖泊-纳木错周缘湖相沉积、湖岸堤的野外调查和湖岸阶地的水准测量,发现在纳木错沿岸拔湖48m以下,发育有6级湖岸阶地,拔湖48~139.2m发育有高位湖相沉积。湖相沉积物的同位素测年结果表明,纳木错湖泊发育与藏北高原东南部古大湖演化可划分为3个阶段:①116~37kaB.P.间的古大湖期;②37~30kaB.P.间的外流湖期;③30kaB.P.以来的纳木错期。根据纳木错晚更新世以来湖相沉积中粘土矿物的X光衍射分析结果,以及采用比值法、高岭石法和衍射峰法的研究,探讨了粘土矿物所显示的环境变化信息。粘土矿物成分变化表明,该区已具备了寒温带干旱、半干旱区的气候环境特征。为研究青藏高原的湖泊演化、气候变化、古地理变迁及其隆升过程等提供了新资料。      

Cretaceous Sandbody Characters at Shallow‐Water Lake Delta Front and the Sedimentary Dynamic Process Analysis in Songliao Basin,China

Based on the abundant information from drilling, cores, and logging, the influence of topography, size of rivers and lakes, climate changes and the lake level’s fluctuation on the sandbodies at shallow-water delta front are systematically summarized and the sedimentary dynamic processes are analyzed. The interwell communication among the sandbodies and their planar distribution revealed from the hydrodynamic features of the development wells are integrated during the analysis. The fundamental requirements for the development of the shallow-water delta included flat topography and uniform subsiding rate. The delta plain was connected smoothly with the wide delta front and predelta, without the three-fold structure of topset, foreset, and bottomset as defined in the Gilbert Delta Model. Because of the weak fluvial effect and the lake energy is strong, the small and scattered shallow-water delta is destroyed by the scouring-backwashing, coastal current, and lake wave, resulting in the coastal sheet deposition. As the fluvial effect became stronger and the lake energy became weaker, the shape of the shallow-water deltas transferred from sheets to lumps and then branches.     

Method of Data Reduction and Uncertainty Estimation for Platinum-Group Element Data Using Inductively Coupled Plasma-Mass Spectrometry

A data reduction method is described for determining platinum-group element (PGE) abundances by inductively coupled plasma-mass spectrometry (ICP-MS) using external calibration or the method of standard addition. Gravimetric measurement of volumes, the analysis of reference materials and the use of procedural blanks were all used to minimise systematic errors. Internal standards were used to correct for instrument drift. A linear least squares regression model was used to calculate concentrations from drift-corrected counts per second (cps). Furthermore, mathematical manipulations also contribute to the uncertainty estimates of a procedure. Typical uncertainty estimate calculations for ICP-MS data manipulations involve: (1) Carrying standard deviations from the raw cps through the data reduction or (2) calculating a standard deviation from multiple final concentration calculations. It is demonstrated that method 2 may underestimate the uncertainty estimate of the calculated data. Methods 1 and 2 do not typically include an uncertainty estimate component from a regression model. As such models contribute to the uncertainty estimates affecting the calculated data, an uncertainty estimate component from the regression must be included in any final error calculations. Confidence intervals are used to account for uncertainty estimates from the regression model. These confidence intervals are simpler to calculate than uncertainty estimates from method 1, for example. The data reduction and uncertainty estimation method described here addresses problems of reporting PGE data from an article in the literature and addresses both precision and accuracy. The method can be applied to any analytical technique where drift corrections or regression models are used.     

一种基于核学习的储集层渗透率预测新方法

基于核学习的支持向量机,是一种采用结构风险最小化原则代替传统经验风险最小化原则的新型统计学习方法,具有完备的理论基础。这里提出了核学习技术在储集层非均质特性描述中渗透率参数预测的新用途。在复杂地层中,基于支持向量机的智能和自适应模式识别能力而建立了常规测井多参数信息输入的渗透率预测模型,然后对实际油田储集层渗透率进行了预测。与常规线性回归模型预测结果相对比,所提出的方法更易于使用,很少受不确定因素的影响,并具有较强的信息整合能力以及更高的预测准确性和可信度。     

全新世岱海流域化学风化及其对气候事件的响应

通过对岱海 12.08 m沉积岩芯 210Pb和 AMS- 14C精确定年及地球化学、物理指标的综合分析,重建了包括 8.2 ka冷期、中世纪暖期 (MWP)和小冰期 (LIA)等典型气候事件在内的全新世以来所经历的化学风化及其环境演化过程.全新世早-中期 (9.0～ 3.5 ka),岱海流域处于温暖湿润气候环境,主要环境特征表现为流域化学风化显著增强、生物生产力逐步提高、湖泊水位大幅度抬升.在 7.90～ 8.25 ka期间存在一次冷气候事件,其发生时间与来自湖沼、海洋、生物组合和极地冰芯等在内的全球环境记录基本一致,具体表现为流域化学风化减弱、湖泊生产力降低以及湖泊水位下降. 2.5 ka以来,岱海沉积物中环境指标的显著变化,表明进入气候波动更频繁的新冰期.岱海沉积物中的指标变化也展示了本世纪以来的气候增暖过程,但其化学风化强度还没有达到 MWP的程度.     

我国湖泊环境演变及其成因机制研究现状

湖泊沉积忠实地记录了湖泊环境变化的各类信息.不同时问尺度的湖泊环境变化分别受到构造、气候与人类活动三个方面的驱动机制的影响.影响中同湖泊环境变化的最主要的构造运动是青藏高原的隆升;气候变化的影响主要是东亚季风系统带来的一系列作用;而人类活动的影响则比较复杂,不仅有流域植被、土壤性质的改变导致输入湖泊物质的变化,也有人类活动直接改造湖泊,如围垦、封堵等.准确地分析湖泊环境变化的各种过程与规律,特别是定量刻画人与自然相互作用下的湖泊环境响应过程与驱动机理,是当今科学界的热点.     

多元门限回归模型的一种建模方法

本文根据门限自回归模型的基本思想[1]，提出一种多元门限回归模型的建模方法。其特点是充分考虑了预报系统中某些特殊预报因子突变点对预报关系的改变作用。数值实例表明，该模型在模拟和预报精度上比一般线性逐步回归模型有一定程度的提高。