Chemical and Sr-Nd compositions and 40Ar/39Ar ages of NW-trending dolerite dikes of Burkina Faso: Evidence for a Mesoproterozoic magmatism in the West African Craton

The Paleoproterozoic basement of the northeastern part of the Leo-Man craton is intruded by generally NW-trending dikes. These regional scale dikes extend over 1000 km in Burkina Faso, Mali and Niger. We present chemical and Sr-Nd isotope compositions, as well as ⁴⁰Ar/³⁹Ar ages of these dikes with the following strikes N98°–N112°, and N114°–N124° in NE Burkina Faso. Field relationships show that the dikes are posterior to all other rock types dated between 2.26 Ga and 2.0 Ga. Chemical data indicate that the dikes are continental flood basalts and composed of low-Ti (TiO₂ ≤ 2 wt.%) sub-alkaline basalts and andesites. They exhibit a minor negative Europium anomaly (0.86–0.99) and slightly fractionated REE patterns ((La/Yb)_N = 2.5–9.1; Yb_N = 9.5–19.9). The ratios of Th/Ta (1.3–11.4) and Ce/Pb (5.2–58.5) suggest a varying crustal assimilation of the dike magmas during ascent in the continental crust for all studied samples. Calculated P-T conditions indicate that the magma reached temperatures of 1285 °C (calculated from olivine compositions) and pressures of 6.9 kbar (calculated for pyroxene minerals). Calculated initial ⁸⁷Sr/⁸⁶Sr (0.70040–0.70260) and ɛ_Nd(t) = +2.1 to −3.5 at 1575 Ma, also point to a crustal contamination with the most primitive samples showing T_DM values of 1946 Ma and 2154 Ma. The low values of La/Ba (<0.2) and Nb/La (<1.0), contrast with the low Th/Nb (<0.9), and suggest a lithospheric mantle or subduction-modified mantle as possible source for the dikes. Sr-Nd data, Mg# and Nb-Ta-Zr-Y-Th-Tb-Yb compositions further suggest that the most primitive samples were emplaced in a none orogenic setting and their magmas were subjected to variable crustal contaminations. Literature and the present whole rock ⁴⁰Ar/³⁹Ar age determinations show that the dikes were emplaced during a widespread Mesoproterozoic magmatism between 1.6 Ga and 1.2 Ga, and were affected by a thermal event causing the argon systematics resetting, best constrained by the date of sample KK1 (1236 ± 20 Ma, ⁴⁰Ar/³⁶Ar = 294 ± 13, MSWD = 2.2). Contemporaneous 1590–1570 Ma extensive magmatism is reported in other crustal blocks in Baltica (Sveconorw-Goth, svecofennian) NW Laurentia (Slave craton, Yukon), and Australia (Gawler craton), and together with the 1575 studied dikes, are related to the breakup of the supercontinent Nuna.     

智能优化LSSVM算法的混沌时间序列边坡变形预测模型

边坡变形序列存在一定混沌特征,本文将混沌分析方法应用到边坡变形预测中。为解决标准LSSVM模型中惩罚参数和核函数参数因任意给定或经验给定带来的非最优问题,将遗传算法和粒子群算法引入LSSVM模型,根据变形序列建立GA-LSSVM和PSO-LSSVM预测模型,与标准LSSVM混沌预测模型和基于神经网络的混沌预测模型进行比较。结果表明,GA-LSSVM和PSO-LSSVM模型预测中误差分别为0.73 mm和0.77 mm,LSSVM,BP,RBF三种模型中误差分别为0.90 mm,0.80 mm和0.75 mm;因此,本文提出的预测模型用于边坡变形预测比其他几种模型具有更高的精度。     

航空摄影测量生产作业流程优化方法

传统的航空摄影测量生产作业流程存在着内业、外业相对独立,采编与图库相互分离等许多缺点。这样,导致较长的生产周期难以提供实时的测量结果,在经济发展快的地区表现得更加严重。本文通过新技术的应用和工作经验总结,进行了生产作业流程优化方法的关键技术讨论,实现了缩短生产周期,提高了生产作业效率。最后,结合应用实例进行效果评价。     

基于有限元分析的松原震群与日本大地震的关系探讨

日本3·11大地震之后,我国松原地区发生了多次4级以上地震,两者之间存在的关系是本文探讨的重点。利用有限元方法,构造两个有限元模型,从库仑应力变化的角度研究日本3·11大地震对位于郯庐断裂带北段第二松花江断裂的影响。模拟结果表明,日本大地震对我国东北部地区影响大,第二松花江断裂带的位移最大达到20 mm。整个研究区的静态库仑应力均为正值,表明该断层处于危险阶段。考虑到实际地壳介质对应变传递的延迟效应,日本3·11大地震对我国东北地区的实际影响会有一个滞后,因此松原震群与日本3·11大地震存在密切相关性。     

一种优化的自由网平差及其在变形监测中的应用研究

主要介绍使用序贯平差与秩亏自由网平差联合的方法对自由网平差进行优化,此优化方法能集合自由网平差无控制点约束的特点和序贯平差处理大数据量的高效率特点.最后通过工程实例具体阐述了将该优化的自由网平差方法应用于变形监测中.     

山区土地流转对缓解耕地撂荒的作用

耕地撂荒是目前山区发展较快的一种土地利用变化,耕地流转能否缓解这一过程,促进土地资源有效配置,以避免耕地资源浪费,是一个值得探讨的课题。借助前期研究成果,使用多视角两因素散点分析和单因素相关分析方法,旨在查明山区耕地流转对缓解耕地撂荒的作用,结果表明:1在村级尺度上,样区耕地流转与耕地撂荒间呈现显著负相关关系,流转率高的村庄,撂荒率低,尤其在优等耕作条件的耕地中表现更为突出,说明耕地流转可以减少优等耕作条件的耕地撂荒;2在地块尺度上,优等耕作条件的耕地撂荒率显著低于劣等耕作条件,样区耕地的撂荒主要由Ⅳ等耕作条件的耕地所贡献;3在村级尺度上,样区耕作条件对耕地撂荒率的作用较弱,村样本间耕作条件对撂荒率差异的解释能力不强,优等耕作条件的耕地撂荒仍然存在,说明以耕地流转率代表的土地租赁市场尚不发育;4但是,样区耕地流转率高的村庄,优等耕作条件的耕地撂荒率低,说明耕地撂荒仍然受到土地租赁市场的完善程度所左右,且土地租赁市场在优化耕地资源利用方面的作用已有一定程度的显现;5进一步完善土地租赁的市场化程度,有助于减少或降低耕地撂荒现象的发生,可以避免优等耕作条件的耕地浪费。     

重庆丘陵地区农村居民点空间布局优化——以长寿区海棠镇为例

以农村居民点斑块为研究单元,在分析海棠镇农村居民点斑块综合影响力的基础上,基于不同地貌,制定差异化的空间布局优化策略,并应用加权Voronoi图指导居民点斑块的迁移方向。结果表明:1海棠镇村级影响力居民点斑块面积183.57 hm2(183个);社级影响力居民点斑块面积206.86 hm2(391个);零星居民点斑块面积31.49 hm2(118个),影响力较大的居民点斑块主要分布在海棠镇中东部地势较平缓的区域;2通过布局优化,全镇农村居民点斑块总面积从优化前的421.92 hm2减少到优化后的353.73 hm2,减少了16.16%;居民点斑块密度由优化前的14.74个/km2降低到8.94个/km2,降低幅度达39.35%;居民点斑块平均面积从优化前的0.61 hm2增大到0.84 hm2,增加了37.70%。海棠镇农村居民点"小散乱"的空间分布现状得到较大改善。     

Inversion of 3D density interface with PSO-BP method

BP( Back Propagation) neural network and PSO( Particle Swarm Optimization) are two main heuristic optimization methods,and are usually used as nonlinear inversion methods in geophysics. The authors applied BP neural network and BP neural network optimized with PSO into the inversion of 3D density interface respectively,and a comparison was drawn to demonstrate the inversion results. To start with,a synthetic density interface model was created and we used the proceeding inversion methods to test their effectiveness. And then two methods were applied into the inversion of the depth of Moho interface. According to the results,it is clear to find that the application effect of PSO-BP is better than that of BP network. The BP network structures used in both synthetic and field data are consistent in order to obtain preferable inversion results. The applications in synthetic and field tests demonstrate that PSO-BP is a fast and effective method in the inversion of 3D density interface and the optimization effect is evident compared with BP neural network merely,and thus,this method has practical value.     

An improved SVM model for relevance feedback in remote sensing image retrieval

With the rapid development of satellite remote sensing technology and an ever-increasing number of Earth observation satellites being launched, the global volume of remotely sensed imagery has been growing exponentially. Processing the variety of remotely sensed data has increasingly been complex and difficult. It is also hard to efficiently and intelligently retrieve what users need from a massive database of images. This paper introduces an improved support vector machine (SVM) model, which optimizes the model parameters and selects the feature subset based on the particle swarm optimization (PSO) method and genetic algorithm (GA) for remote sensing image retrieval. The results from an image retrieval experiment show that our method outperforms traditional methods such as GRID, PSO, and GA in terms of consistency and stability.     

Non‐linear prestack seismic inversion with global optimization using an edge‐preserving smoothing filter

Estimating elastic parameters from prestack seismic data remains a subject of interest for the exploration and development of hydrocarbon reservoirs. In geophysical inverse problems, data and models are in general non‐linearly related. Linearized inversion methods often have the disadvantage of strong dependence on the initial model. When the initial model is far from the global minimum, inversion iteration is likely to converge to the local minimum. This problem can be avoided by using global optimization methods. In this paper, we implemented and tested a prestack seismic inversion scheme based on a quantum‐behaved particle swarm optimization (QPSO) algorithm aided by an edge‐preserving smoothing ( EPS) operator. We applied the algorithm to estimate elastic parameters from prestack seismic data. Its performance on both synthetic data and real seismic data indicates that QPSO optimization with the EPS operator yields an accurate solution.