基于自适应遗传算法的超平面分类及遥感应用

智能分类算法是遥感影像分类研究的热点,遗传算法作为一种智能全局优化技术在遥感影像分类中具有良好应用前景.针对现有多光谱遥感影像分类方法的不足,提出了基于自适应遗传算法的超平面分类方法(hyper plane-adaptive genetic algorithm,HP-AGA)并应用于遥感影像分类,该方法利用神经网络中的神经元激活函数Sigmoid函数,对遗传算法中交叉率、变异率进行非线性自适应性调整,不再需要反复训练遗传参数,同时利用快速全局寻优特点,确定分类超平面的各个位置参数,从而获取最佳分类超平面集进行分类.多光谱遥感影像分类方法的应用实验表明,基于自适应遗传算法的超平面遥感分类方法能更快、更稳定地收敛到全局最优解,具有更好的效率及鲁棒性,并能取得优于简单遗传超平面分类算法及传统分类方法的分类精度.     

Global vegetation change analysis based on MODIS data in recent twelve years①

Vegetation cover change is critical for understanding impacts and responses of vegetation to climate change. A study found that vegetation in the regions between 45°N-70°N was increasing using normalized difference vegetation index( NDVI) from 1981 to 1991 ten years ago. The global vegetation growth has changed because of climate change in recent twelve years( 2001- 2012). After thorough analysis based on satellite data,it is found that it is evident that the global vegetation changed( NDVI) little,and it is increasing slightly in Northern hemisphere while it is decreasing slightly in Southern Hemisphere. For different latitudes,vegetation is increasing 0.17% every year from 60°N to 70 °N( R~2= 0.47,P 0.013),while the vegetation is decreasing 0.11% every year from 10°N to 10° S( R~2= 0.54,P 0.004). For different continents,the vegetation in South America is decreasing 0.16% every year( R~2= 0.78,P 0.0001) and it is increasing 0.05% every year in Asia( R~2= 0.28,P 0.072) and 0.25% every year in Oceania( R~2= 0.24,P 0.1). The analysis of global vegetation in different seasons indicates that spatial distribution of global temperature and water vapor will affect the spatial distribution of vegetation,in turn,the spatial distribution of vegetation will also regulate the global temperature and water vapor spatial distribution at large scale. The growth and distribution of vegetation are mainly caused by the orbit of the celestial bodies,and a big data model based on gravitational-magmatic change with the solar or the galactic system as its center is proposed to be built for analyzing how the earth's orbit position in the solar and galaxy system affects spatial-temporal variations of global vegetation and temperature at large scale. These findings promise a holistic understanding of the global climate change and potential underlying mechanisms.     

企业数字电视整体转换的方式——以山西焦煤汾西矿业集团公司为例

以山西焦煤汾西矿业集团公司为例,详细介绍了企业数字电视整体转换的方式,讨论了企业数字电视网络改造中的实际运作,以期为其他案例提供借鉴。     

浅谈建筑节能改造的防火问题

既有建筑节能改造是当前我国建筑节能工作的重点,但由于材料、施工、法规监管等多方面的原因,给我国建筑防火安全造成了许多重大隐患和事故。就如何在建筑节能改造中通过多种手段处理好防火安全问题进行了讨论,提出一些可供借鉴的方法。     

Temporal and spatial distribution of tropospheric CO<Subscript>2</Subscript> over China based on satellite observations

Mid-troposphere CO₂ data retrieved by the AIRS (atmospheric infrared sounder) were validated with five ground-based stations and aircraft measurements in the Northern Hemisphere. AIRS CO₂ products show good agreement with ground and aircraft observations. The data had a monthly average accuracy better than 3 ppmv. In this study, the spatial and temporal distribution of mid-troposphere CO₂ from January 2003 to December 2008 was analyzed based on this satellite product. The average concentration of atmospheric CO₂ was higher in the Northern Hemisphere than in the Southern Hemisphere. The yearly average results show a gradual increase from 2003 to 2008. In China, the annual growth rate was about 2 ppmv/a, similar to the United States, Europe, Australia and India, but was slightly lower than Canada and Russia. Mid-troposphere CO₂ concentrations were higher over northern China than over southern areas, due to differences in natural conditions and industrial layout. There were four centers of high CO₂ concentration between 35° and 45°N over China, with low concentrations over Yunnan Province. There was a significant seasonal CO₂ variation with peak concentration in spring and the lowest concentration in autumn.     

陵川县供水改扩建工程枢纽坝型分析与比选

在概述陵川县供水改扩建工程情况的基础上,进行了枢纽坝型的比选。     

基于AIS信息融合的船载航行数据记录再现

研究VDR与AIS信息融合的信息再现,分析VDR和AIS播发的信息及其系统结构,设计了基于AIS信息融合的船载航行数据记录再现系统,并介绍了系统的构成、技术以及功能.     

Dempster-Shafer （D-S） algorithm with credit scale in spectrum sensing

In cognitive radio, the detection probability of primary user affects the signal receiving performance for both primary and secondary users significantly. In this paper, a new Dempster-Shafer (D-S) algorithm with credit scale for decision fusion in spectrum sensing is proposed for the purpose to improve the performance of detection in cognitive radio. The validity of this method is established by simulation in the environment of multiple cognitive users who know their signal to noise ratios (SNR) and a central node. The channels between the cognitive users and the central node are considered to be additive white Gaussian noise (AWGN). Compared with traditional data fusion rules, the proposed D-S algorithm with credit scale provides a better detection performance.     

图像超分辨率重建算法比较研究

针对超分辨率重建技术的基本理论以及研究现状给予了综述性研究,对当前的主要算法进行了比较分析.     

基于SIFT的二视图运动与结构的恢复

针对传统二视图三维重构所体现出来的问题,综合各种重构方法,给出了一种简单的二视图运动与结构恢复的过程;且将SIFT特征点提取和匹配的方法应用到运动与结构恢复当中.实验过程和结果表明,该过程简单有效,具有一定的应用价值.