移动互联网时代防震减灾科普宣传的问题及对策研究     

李晓丽 《高原地震》2014,(1):54-58

在移动互联网蓬勃发展的信息技术背景下,我国防震减灾科普教育存在若干问题,如忽视受众的"数字化"特征,基于智能终端的宣传材料不足;宣传手段不能满足移动互联网时代信息化要求;宣传内容不够生动等,因此提出防震减灾科普知识泛在化宣传新模式,并根据泛在化宣传模式的特征,设计开发基于iOS系统的泛在化宣传资源,为防震减灾宣传工作提供基于移动设备的数字化资源支持。该研究对移动互联网时代地震科普宣传作了新的探讨与尝试,对于当前及未来全民普及防震减灾科学知识有积极的促进作用。  相似文献   

Seafloor Classification of Multibeam Sonar Data Using Neural Network Approach     

Xinghua Zhou  Yongqi Chen 《Marine Geodesy》2013,36(2):201-206

In this study, the self-organizing map (SOM), which is an unsupervised clustering algorithm, and a supervised proportional learning vector quantization (PLVQ), are employed to develop a combined method of seafloor classification using multibeam sonar backscatter data. The PLVQ is a generalized learning vector quantization based on the proportional learning law (PLL). The proposed method was evaluated in an area where there are four types of sediments. The results show that the performance of the proposed method is better than the SOM and a statistical classification method.  相似文献   

地震干涉技术被动源地震成像   总被引：2，自引：0，他引：2  

朱恒  王德利  时志安  冯飞 《地球物理学进展》2012,27(2):496-502

被动源地震成像是基于地下反射波响应和透射波响应之间的关系,通过在地表接收由地下非人工震源发出的透射波响应,利用互相关运算来合成反射波响应的方法.合成的反射波响应,又称虚炮集记录等价于地表地震剖面记录.本文研究了由地下随机分布的被动源发出的透射波记录来合成虚炮集记录的基本原理,推导了反射波记录和透射波记录的关系公式;并通过数值模拟方法,分析了被动源成像的可行性.结果表明:利用被动源地震信息进行成像是可行的.  相似文献   

Radial Basis Functional Link Nets Used as a Prospectivity Mapping Tool for Orogenic Gold Deposits Within the Central Lapland Greenstone Belt, Northern Fennoscandian Shield   总被引：1，自引：0，他引：1  

Vesa Nykänen 《Natural Resources Research》2008,17(1):29-48

Among the more popular spatial modeling techniques, artificial neural networks (ANN) are tools that can deal with non-linear relationships, can classify unknown data into categories by using known examples for training, and can deal with uncertainty; characteristics that provide new possibilities for data exploration. Radial basis functional link nets (RBFLN), a form of ANN, are applied to generate a series of prospectivity maps for orogenic gold deposits within the Paleoproterozoic Central Lapland Greenstone Belt, Northern Fennoscandian Shield, Finland, which is considered highly prospective yet clearly under explored. The supervised RBFLN performs better than previously applied statistical weights-of-evidence or conceptual fuzzy logic methods, and equal to logistic regression method, when applied to the same geophysical and geochemical data layers that are proxies for conceptual geological controls. By weighting the training feature vectors in terms of the size of the gold deposits, the classification of the neural network results provides an improved prediction of the distribution of the more important deposits/occurrences. Thus, ANN, more specifically RBFLN, potentially provide a better tool to other methodologies in the development of prospectivity maps for mineral deposits, hence aiding conceptual exploration.  相似文献   

基于反褶积算法的地震干涉技术被动源成像     

王德利  程浩  朱恒  冯飞 《吉林大学学报(地球科学版)》2012,42(6):1920-1926

地震干涉技术可以将任意2个检波器接收到的数据合成为在若干检波器之间传播的波,就好像其中的一个检波器作为一个虚拟震源来发挥作用。它可以从混沌无序的地震信号中发现有用信息,从地震噪声中提取有用信号以此推断地震波穿过介质的地质构造。基于反褶积算法,对其理论公式进行了较详细的推导,实现被动源地震干涉成像,证明了反褶积算法的可行性;并将其结果与互相关算法的结果进行对比,分析了2种方法在信噪比和分辨率方面的差异。数值计算表明,反褶积算法的纵向分辨率比互相关算法的高。对其进行的加噪试算表明,震源叠加后的反褶积算法呈现出高信噪比的特点。  相似文献   

面向电网巡检的多旋翼无人机航测系统关键技术研究及应用   总被引：2，自引：0，他引：2  

汤坚  杨骥  宫煦利 《测绘通报》2017,(5):67-70

针对无人机电力巡检所面临的定位精度低、近距离巡检操控难度大、自动化程度低、人为操控事故风险高等问题,本文提出了利用多旋翼无人机RTK差分定位技术、复杂塔型飞行规则机器学习算法等无人机航测系统技术,研发面向电网巡检的无人机智能操作系统及控制终端,提升电网线路日常管理和应急指挥的规范性、便利性和经济性,为电网管理部门提供一种低成本、易操作、高效率、机动灵活的新型巡检模式。  相似文献   

翻转课堂在地理信息系统课程教学中的实践与思考     

王建梅  王卫安 《测绘通报》2017,(8):146-149

针对教师主导的传统教学模式在地理信息系统课程教学中存在的不足,提出了将翻转课堂这一新的混合学习教学模式引入教学的想法。首先分析了地理信息系统课程实施翻转课堂的必要性和可行性,然后在综合考虑地理信息系统课程特点与中外教育文化差异的基础上进行了课程设计和组织实施。实践结果表明,实施翻转课堂确实能够提高学生学习主动性和教学质量,同时也对教师的专业水平和教学能力提出了更高的要求。  相似文献   

Effects of misclassification costs on mapping mineral prospectivity     

《Ore Geology Reviews》2017

Mineral prospectivity mapping is a classification process because in a given study area, a specific region is classified as either a prospective or non-prospective area. The cost of false negative errors differs from the cost of false positive errors because false positive errors lead to wasting much more financial and material resources, whereas false negative errors result in the loss of mineral deposits. Traditional machine learning algorithms using for mapping mineral prospectivity are aimed to minimize classification errors and ignore the cost-sensitive effects. In this study, the effects of misclassification costs on mapping mineral prospectivity are explored. The cost-sensitive neural network (CSNN) for minimizing misclassification costs is applied to map Fe polymetallic prospectivity in China’s southwestern Fujian metalorganic belt (SFMB). A CSNN with a different cost ratio ranging from 1:10 to 10:1 was used to represent various misclassification costs. The cross-validation results indicated a lower misclassification cost compared to traditional neural networks through a threshold-moving based CSNN. The CSNN’s predictive results were compared to those of a traditional neural network, and the results demonstrate that the CSNN method is useful for mapping mineral prospectivity. The targets can be used to further explore undiscovered deposits in the study area.  相似文献   

Charting the emergence of a ‘knowing system’ for climate change adaptation in Australian regional natural resource management     

《Geoforum》2017

Climate change increases the complexity and uncertainty of regional natural resource management (NRM), calling into question the appropriateness of linear knowledge-transfer approaches. In this paper we reflect on knowledge practices among a partnership of researchers and NRM planners, under a federal program of NRM investment intended to ‘deliver information’ to regional NRM planners to support planning for climate change. We unpack ‘container’ and ‘conduit’ metaphors of linear, one-way communication invoked by the starting conditions, and explore whether more relational ways of communicating were achieved. A key theme emerged early in the research that NRM planners felt overwhelmed by the sheer volume of information available and discouraged by the irrelevance of much of it to their climate change planning. Our research-practice collaboration unfolded in this context and through ongoing face-to-face and virtual engagement over a period of two years. The collaborative approach featured joint identification of priority activities, co-design of planning approaches, and the iterative co-development of an online ‘information portal’, which acted as a boundary object. We report the emergence of a ‘knowing system’, resulting from these efforts to foster relationships and co-produce boundary objects in a particular geographic context. Our findings highlight the potential benefits of investing in the capacity of researchers and NRM practitioners to engage in collaborative research partnerships premised on the emergence of knowing systems.  相似文献   

基于深度学习的区域生态安全时空模拟与预测     

陈工  李琦  金玲艳  梁贺明  莫玉琴 《地球信息科学学报》2017,19(7):915-923

区域作为人类、自然、社会共同作用和互相影响的复杂系统,对区域进行生态量化建模与模拟仿真,是实现区域可持续发展战略的关键。传统机器学习方法对区域生态系统建模取得了一定的成果,但难以确定学习特征和实现时空模拟。深度学习不需事先确定训练特征,具有优异的特征学习能力,能够提高模型预测精度,因此利用深度学习进行建模具有显著优势。本文使用植被净初级生产力（NPP）、气溶胶光学厚度（AOD）和人口格网数据,充分利用深度学习的优点,采用最优深度神经网络时空模拟,得到了河南省2007-2014年3 km分辨率的生态赤字空间分布图和河南省2015-2020年的生态赤字时间预测结果并进行分析,为区域生态的科学管理和建设供科学依据和参考。  相似文献