Enhancing group resolution of TM6 based on multi-variate regression model and semi-variogram function

It is well known that Landsat TM images are the most widely used remote sensing data in various fields. Usually, it has 7 different electromagnetic spectrum bands, among which the sixth one has much lower ground resolution compared with the other six bands. Nevertheless, it is useful in the study of rock spectrum reflection, geo-thermal resources exploration, etc. To improve the ground resolution of TM6 to the level as that of the other six bands is a problem. This paper presents an algorithm based on the combination of multi-variate regression model with semi-variogram function which can improve the ground resolution of TM6 by “fusing” the data of other six bands. It includes the following main steps: (1) testing the correlation between TM6 and one of TM1-5, 7. If the correlation coefficient between TM6 and another one is greater than a give threshold value, then select the band to the regression analysis as an argument. (2) calculating the size of the template window within which some parameters needed by the regression model will be calculated; (3) replacing the original pixel values of TM6 by those obtained by regression analysis; (4) using image entropy as a measurement to evaluate the quality of the fused image of TM6. The basic mechanism of the algorithm is discussed and the V C++ program for implemeting this algorithm is also presented. A simple application example is given in the last part of this paper, showing the effectiveness of the algorithm.     

Application of the honey-bees mating programming (HBMP) algorithm to sediment concentration modelling

Abstract

The honey-bees mating programming (HBMP) algorithm is introduced as a novel tool for predicting suspended sediment concentration for the Mad River catchment near Arcata, USA. The paper also applies gene expression programming (GEP) as a comparison and shows that these two approaches can the produce transparent, nonlinear relationships between the independent and dependent variables. Some modifications have been made to the HBMP algorithm to improve its capability and efficiency. The results achieved from this method and GEP are compared with two different sediment rating curves based on regression techniques. The findings show that the results from both the HBMP and GEP methods are promising and outperform the results obtained from the sediment rating curves.

Editor D. Koutsoyiannis; Associate editor L. See     

加速遗传算法在预应力连续箱梁桥有限元模型修正中的应用

针对预应力混凝土连续箱梁桥的通扬运河大桥,建立其有限元模型.基于评价模型修正效果的频率指标与振型相关系数指标、柔度矩阵指标和挠度指标,定义三个目标函数,利用环境激励的试验模态参数,通过实数编码加速遗传算法对有限元模型进行了修正.相对于基于频率指标与振型相关系数指标定义的目标函数,基于柔度矩阵指标或挠度指标定义的目标函数修正的有限元模型,能同时较准确地反映其动态和静态特性,也能实现其试验模态振型较精确的质量归一化.     

2009年姚安6.0级地震序列研究

2009年7月9日在云南省姚安县发生M6.0地震,利用云南区域数字地震台网记录的ML≥2.0余震波形记录,通过对S波观测记录谱进行传播路径、场地响应和仪器响应等影响的逐一消除,得到131个地震的震源谱.进而根据Brune圆盘震源模型,利用遗传算法计算地震矩、应力降、震源半径等震源参数.结果表明,该地震序列的M0在1012-1016N·m,与近震震级有很好的线性关系,与震源半径呈线性关系;应力降与近震震级有一定线性趋势相关性;拐角频率和地震矩M0之间有明显的依赖关系.     

基于区间直觉模糊数的地震应急服务点选址模型

地震应急物资储备服务点选址是地震应急救援决策工作的重要基础。本文分析了地震应急服务点选址问题的不确定性,介绍了直觉模糊数和区间直觉模糊数的概念,在分析两者之间关系的基础上,定义了区间直觉模糊数的得分函数和精确函数,进而提出了基于得分函数和精确函数的区间直觉模糊数的排序规则;行车时间受诸多因素影响,将行车时间看成区间直觉模糊信息,构建了约束中含有区间直觉模糊参数的地震应急服务点选址模型,提出了一种基于区间直觉模糊数排序规则的模型算法,可得到地震应急服务点最优选址方案。通过算例分析验证了该方法的有效性。     

A spatial approach to forest‐management optimization: linking GIS and multiple objective genetic algorithms

Forest‐management decision‐support systems are largely monolithic structures. Spatial details are left out during the optimization process and are elaborated during the operational planning. This might produce misleading results and plans that are impossible to implement. In this paper, a forest‐management spatial decision‐support systems is presented, in which spatial formulation needed for wildlife models is included during the optimization process. To this end, a multiple‐objective genetic algorithm is combined with a geographical information system. An online spatial evaluation of the objective functions is made possible. This is illustrated by a pilot study in Kirkhill forest, Aberdeen.     

川西坳陷中段上三叠统须二段致密砂岩孔隙度演化史

川西坳陷深层上三叠统须家河组经历的地史时间长,构造期次多,成岩作用改造普遍,储层致密化严重,导致致密砂岩气藏成因机制研究困难,其中孔隙度演化史的研究是该区致密气藏成因类型的判识和天然气勘探的关键。在利用显微镜观察、扫描电镜分析、阴极发光分析等认识了储层成岩作用特征的基础上,结合自生矿物中流体包裹体的均一化温度和古地温梯度等,建立了须二段储层的成岩作用序列,并确定了成岩矿物形成时间。在充分考虑沉积过程中的粒度、分选性等岩相特征对原生孔隙的影响,及压实作用、胶结和溶蚀等成岩作用对孔隙度演化的影响前提下,分成岩作用阶段建立了孔隙度演化的定量模型。研究结果表明,川西坳陷须二段储层致密化时间较早,一般在晚成岩作用早期,即晚侏罗世的早期已经基本致密化,但不同的气藏由于储层的岩相特征和成岩作用特征存在差异,导致储层致密化时间存在一定差异。     

山东张里金矿碱性次火山岩特征与成矿作用

山东张里金矿床是与碱性次火山岩有关的、赋存于隐爆角砾岩体内的石英－ 冰长石－ 萤石型中低温热液矿床。岩石化学、稀土元素和同位素分析结果表明: 控矿岩石系列分为: ①高钾钙碱性岩石系列,SiO2 平均含量为57. 6%,稀土总量为373. 98 × 10 － 6 ～ 297. 43 × 10 － 6,δEu 为0. 85 ～ 0. 82,Sr = 0. 704 41; ②高钾碱性岩系列,SiO2 平均含量为56. 65%,稀土总量为371. 19 × 10 － 6 ～ 41. 62 × 10 － 6, δEu 为0. 89 ～ 0. 93,Sr = 0. 717 11。这两种控矿岩石系列分别由两个不同的幔源岩浆在上升过程中,各自经过长时期的分异作用,并且混染了部分壳源物质而成,其含矿热液来自碱性次火山岩。     

安徽江淮地区土壤微量元素分布特征及成因分析

多目标区域地球化学调查作为生态地球化学调查的基础工作,以快速查明表层土壤及其背景地球化学元素分布为目的.本文以安徽江淮地区多目标区域地球化学调查结果为基础,对安徽江淮地区耕地土壤及其母质中主要元素分布特征及其成因进行了分析研究,结果得出:(1)大多数地区表层土壤微量元素含量与深层具有一致性和继承性;(2)各地土壤微量元素分布特征主要受成土母质类型控制,说明其成因与成土母质和成土过程等因素有关;(3)耕地土壤微量元素含量的变异受施肥、灌溉和耕作方式等人为因素影响较大,且存在较大的地区差异性.     

基于投影寻踪技术的矿井突水水源判别模型——以新庄孜煤矿为例

投影寻踪是一种降维处理技术,它可以将高维分析问题通过投影方向转化为低维问题分析.应用该法的关键在于寻求最佳投影方向,这可以转化为一个复杂的非线性优化问题,结合Matlab的遗传算法工具箱进行优化求解.本文以淮南新庄孜煤矿为例,建立突水水源判别投影寻踪模型,并与模糊综合评判模型、神经网络模型、灰色聚类模型进行分析比较.结果表明:投影寻踪判别模型能够有效地判别突水水源,比模糊综合评判、神经网络模型、灰色聚类模型具有更高的准确性,为矿井突水水源判别提供了一个新途径.