The FAM(Fuzzy Asociative Memory)neural network model and its application in earthquake prediction

ＴｈｅＦＡＭ（ＦｕｚｚｙＡｓｏｃｉａｔｉｖｅＭｅｍｏｒｙ）ｎｅｕｒａｌｎｅｔｗｏｒｋｍｏｄｅｌａｎｄｉｔｓａｐｐｌｉｃａｔｉｏｎｉｎｅａｒｔｈｑｕａｋｅｐｒｅｄｉｃｔｉｏｎＷＥＩＷＡＮＧ１）（王炜）ＧＥＮＧＦＥＮＧＷＵ２）（吴耿锋）ＢＩＮＳＨＵＨ...     

塔里木盆地深探井完井方法研究

油气井完井方法是完井技术的重要组成部分，从影响完井方法选择的各种因素出发，建立了完井方法数据库及其管理系统，在这基础之上，研制ＣＭＥＳ专家系统及模糊综合评判系统，运用这两个系统可避免过去仅凭经验确定完井方法的不足，使完井方法的研究向定量化，计算机程序化方向前进了一步，研制的系统应用于塔里木盆地深探井完井方法的优选，实践证明是正确，可行的。     

专家系统中的语义及其可信度

针对淮河中游防洪调度决策的实例，用最高低水位经分段折算，作了语义量化；根据方法库模拟结果来判断某种状态的语义可信度，由半正态分布隶属函数来确定；对各种 状的语义可信度间的转换，采用了模糊聚类的方法。     

Influence of neighbourhood information on ‘Local Climate Zone’ mapping in heterogeneous cities

Local climate zone (LCZ) mapping is an emerging field in urban climate research. LCZs potentially provide an objective framework to assess urban form and function worldwide. The scheme is currently being used to globally map LCZs as a part of the World Urban Database and Access Portal Tools (WUDAPT) initiative. So far, most of the LCZ maps lack proper quantitative assessment, challenging the generic character of the WUDAPT workflow. Using the standard method introduced by the WUDAPT community difficulties arose concerning the built zones due to high levels of heterogeneity. To overcome this problem a contextual classifier is adopted in the mapping process. This paper quantitatively assesses the influence of neighbourhood information on the LCZ mapping result of three cities in Belgium: Antwerp, Brussels and Ghent. Overall accuracies for the maps were respectively 85.7 ± 0.5, 79.6 ± 0.9, 90.2 ± 0.4%. The approach presented here results in overall accuracies of 93.6 ± 0.2, 92.6 ± 0.3 and 95.6 ± 0.3% for Antwerp, Brussels and Ghent. The results thus indicate a positive influence of neighbourhood information for all study areas with an increase in overall accuracies of 7.9, 13.0 and 5.4%. This paper reaches two main conclusions. Firstly, evidence was introduced on the relevance of a quantitative accuracy assessment in LCZ mapping, showing that the accuracies reported in previous papers are not easily achieved. Secondly, the method presented in this paper proves to be highly effective in Belgian cities, and given its open character shows promise for application in other heterogeneous cities worldwide.     

Using spectrum differentiation and combination for target detection of minerals

Among the techniques that have been developed in spectroscopy, derivative analysis is particularly promising for use with remote sensing data. In the first step of this research we apply the derivative spectrum in a real hyperspectral image and introduce a new target detection approach called “DCEM”. For this purpose, 1st to 5th orders of derivative spectrum were applied to the DCEM. The outcome of this research has shown that the application of derivative spectrum in target detection is perfectly advisable in a specific derivative order for each target. This order can be introduced as an optimized order or the Best DCEM. The spectrum differentiation eliminates low frequency components of the spectrum. Despite the little information included in those low frequency components of a signal or spectrum, their complete elimination cause an information loss problem. Hence, in the second step of this research an ensemble classifier approach was employed for the combined use of both spectra and the best derivative order. This simultaneous use of the derivative and zero order spectra is introduced as “ECEM”. Experiments were conducted via a HyMap hyperspectral airborne image in eastern Iran. The detection results show that both proposed methods significantly outperform CEM in ROC and AUC values. The best performance upgrade in DCEM detection was about 24% for Kaolinite target and about 28% for Alunite target in ECEM.     

深度学习的半监督遥感图像检索

遥感图像数据的海量性、多样性和复杂性等特点对遥感图像检索的速度和精度提出了更高的要求,其中特征提取是影响遥感图像检索效果的关键。本文方法首先对遥感图像进行预处理,然后基于稀疏自动编码的方法在大量未标注的遥感图像上进行特征学习得到特征字典,基于卷积神经网络的思想,使用训练出来的特征字典对遥感图像进行卷积和池化得到每幅图像的特征图;接下来使用特征图训练Softmax分类器;最后对待检索图像分类,在同一类别中计算特征间的距离,进而实现遥感图像的检索。实验结果表明,该方法能够有效提高遥感图像检索的速度和准确度。     

Drivers of Change and Sustainability in Linked Social–Ecological Systems: An Analysis in the Volta River Basin of Ghana,West Africa

Understanding the nature and relative importance of various drivers of change is crucial for sustainable management of natural resources and in prioritizing management efforts, allocating limited resources, and understanding cumulative effects. For this article, we employed structured an expert judgments approach to identify, characterize, and assess the relative importance of the key biophysical and socioeconomic drivers of change within the Volta River Basin, West Africa. Precipitation variability, water availability, land use change, drought events, and population growth were perceived as most important, while biodiversity loss, social conflicts, pest and disease occurrence, urbanization, and pollution were viewed as less critical. A majority of these drivers were characterized as “slow” acting processes as compared to rapidly changing drivers. Intra- and interexpert groups agreement were found to be significant and convergent, indicating the reliability of the results. The implications of these results for sustainable water resources management and agricultural production are discussed.     

基于决策规则的遥感影像土地利用信息提取

遥感作为近几十年迅速发展起来的一门综合性技术学科,己经在许多领域发挥了重大作用。通过对遥感数据进行专题分类处理以得到土地利用等专题信息是遥感最广泛的应用领域之一。尽管土地利用遥感分类方法不断发展,但分类技术始终跟不上遥感技术本身的发展。本论文的主要目标之一就是以沈阳矿区为研究区,利用多源遥感数据结合地面实地调查,围绕遥感图像,采用常规的最大似然分类法,同时采用选用决策树分类方法,对不同数据源得到的信息进行综合分析,充分利用其中的光谱信息、地学知识以及人的经验知识进行土地利用分类,从而更好地为地方土地有效利用提供决策依据。     

GIS辅助下的基于数据挖掘的林型遥感分类方法研究

在植被分类领域,各类植被光谱特征非常相近,纹理特征比较单一,并且受物候影响较大,使得影像上林地信息的分类识别的成为一个较复杂的过程。本文利用GIS平台构建由影像、DEM等组成的多元空间数据库,将数据挖掘的方法引入林型遥感分类中,充分利用了现有的空间数据资源,减少了同物异谱、异物同谱对林型遥感分类的影响,增强了分类知识获取的自动化和智能化程度。实验结果表明,该方法具有简化知识获取过程和提高分类精度等优点。     

基于雷达回波区域跟踪算法的临近预报技术进展

目前,临近预报技术主要包括外推技术、数值预报技术以及概念模型预报技术等。而业务上主流的临近预报技术以外推为主,主要以雷达资料为基础,采用雷达回波单体质心跟踪算法或雷达回波区域跟踪算法,得到雷达回波以及降水的临近外推预报。本文详细介绍了3种基于雷达回波区域跟踪算法(交叉相关回波跟踪算法、光流法和变分回波跟踪算法)的临近预报技术的国内外研究进展和基本原理。大量的研究和业务实践结果表明,雷达回波区域跟踪算法作为临近预报专家系统的核心部分,在对流天气临近预报方面有较好的可预报性,在临近预报业务时效内,外推预报结果和实况接近,优于数值模式预报。而通过对算法的不断改进,可以提升各临近预报专家系统在临近预报方面的性能。随着天气雷达技术的不断进步,天气雷达在硬件和软件两方面都逐步改进,雷达资料的数据质量明显提高,在对流天气临近预报上,基于雷达回波的区域跟踪技术会凸显其明显优势。