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51.
依托“西部煤炭资源高精度三维地震勘探技术”项目工程,对晋城某矿南翼大巷东南区5m×5m×1ms的三维地震数据体,采用三维地震属性参数预测煤层厚度及其变化规律:沿3煤层、15煤层10ms时窗提取地震属性42种,根据钻孔资料,计算出煤厚与地震属性相关系数;从中优选出相关系数大于0.35的地震属性,其中3煤层9个、15煤层10个;然后进行地震属性互相关分析,优选出与3煤、15煤层厚度相关系数较大的4种属性,建立预测煤厚的BP神经网络模型,分别选取3煤层12个、15煤层4个实测数据作为学习训练和测试样本,以钻孔地震属性作为学习样本,对网络进行训练,最终获得全区煤层厚度。经与预留钻孔成果资料对比,预测精度较高,结果可用。  相似文献   
52.
The application of neural networks as classifiers of seismic events is described with the aim of developing an automatic system for the classification of explosion quakes at the Stromboli volcano. The architecture of the network that we trained to identify four different classes of shocks was a Multi-Layer Perceptron, using the Back Error Propagation algorithm. Five different approaches for representing the information embedded in the seismograms, both in the time and in the frequency domain, were considered, and the results compared. The direct use of the time series of the shocks was not satisfactory. The auto-correlation function worked well, but in some cases it was misleading. A better performance was obtained with a frequency domain representation. Finally, the use of the envelope function did not work well. Combining parameters such as the auto-correlation and envelope functions can improve one source of error, but it may introduce new ones. The performance obtained highlights the importance of the data attributes used for the training of the network. Topologies with eight neurons in a single hidden layer gave, on average, the best results among the considered neural network structures. The overall results provide a large number of events (89% with the best performance) correctly classified, indicating that this automatic technique is reliable, and encouraging further applications in the field of volcanic seismology.  相似文献   
53.
利用地球化学数据,运用人工神经网络方法对美国密苏里州东南Bonneterre组(寒武纪)滨海相的白云岩进行了分类、识别,判别率达100%,结果表明,该方法性能良好,可望成为岩石分类、判别的有效手段。  相似文献   
54.
Elaine Stratford 《Geoforum》2006,37(2):273-286
Baldacchino [Baldacchino, G., 2002. Jurisdictional self-reliance for small island territories: considering the partition of Cyprus, The Round Table, 365, 349-360] has argued that the ‘troika’ of smallness, insularity and peripherality may incline island peoples (rather more than mainlanders?) to question the effects of economic globalization and be especially disposed to innovative approaches to development. He views jurisdictional capacity as integral to that task. Much of the literature on such issues relates to island nations, but this work focuses on Australia’s smallest and only island state of Tasmania, and thus on a sub-national jurisdiction. In what follows I explore the effects of an attempt to enrol Tasmanians in the creation and stabilization of a ‘2020 vision’ meant to be global in its reach, to focus on the particular strengths of the island state, and be innovative in advancing sustainable development. Known as Tasmania Together, the 20-year strategic vision outlines diverse economic, social and environmental goals assembled over two years via widespread consultations with the island’s communities of place and interest. For a time Tasmania Together generated significant debate about what it means to be an island people, and whether and to what extent Tasmanians’ future will be secured through economic globalization or localized endeavours premised on sustainability principles. Important to Tasmanians as well as to island studies, these rhetorics of social and spatial engagement also have salience beyond the borders of the island state, highlighting larger questions about the technologies of governmentality, agency and the performance of identity.  相似文献   
55.
Application of back-propagation networks in debris flow prediction   总被引:6,自引:0,他引:6  
Debris flows have caused serious loss of human lives and a lot of damage to properties in Taiwan over the past decades. Moreover, debris flows have brought massive mud causing water pollution in reservoirs and resulted in water shortage for daily life locally and affected agricultural irrigation and industrial usages seriously. A number of methods for prediction of debris flows have been studied. However, the successful prediction ratio of debris flows cannot always maintain a stable and reliable level. The objective of this study is to present a stable and reliable analytical model for occurrence predictions of debris flows. This study proposes an Artificial Neural Networks (ANN) model that was constructed by seven significant factors using back-propagation (BP) algorithm. These seven factors include (1) length of creek, (2) average slope, (3) effective watershed area, (4) shape coefficient, (5) median size of soil grain, (6) effective cumulative rainfall, and (7) effective rainfall intensity. A total of 178 potential cases of debris flows collected in eastern Taiwan were fed into the ANN model for training and testing. The average ratio of successful prediction reaching 93.82% demonstrates that the presented ANN model with seven significant factors can provide a stable and reliable result for the prediction of debris flows in hazard mitigation and guarding systems.  相似文献   
56.
The stochastic nature of the cyclic swelling behavior of mudrock and its dependence on a large number of interdependent parameters was modeled using Time Delay Neural Networks (TDNNs). This method has facilitated predicting cyclic swelling pressure with an acceptable level of accuracy where developing a general mathematical model is almost impossible. A number of total pressure cells between shotcrete and concrete walls of the powerhouse cavern at Masjed–Soleiman Hydroelectric Powerhouse Project, South of Iran, where mudrock outcrops, confirmed a cyclic swelling pressure on the lining since 1999. In several locations, small cracks are generated which has raised doubts about long term stability of the powerhouse structure. This necessitated a study for predicting future swelling pressure. Considering the complexity of the interdependent parameters in this problem, TDNNs proved to be a powerful tool. The results of this modeling are presented in this paper.  相似文献   
57.
This paper focuses on a case study of an 'alternative' food network based in the Abruzzo National Park, Italy, to explore how ideas of sustainable farmland management can be expressed through broader understandings of developing networks of care concerned with local economies and societies, high-quality specialist food products, particular 'traditional' farming practices and livestock breeds, as well as the ecology of a farmed landscape. The scheme allows customers, internationally as well as in Italy, to 'adopt' a milking sheep on a large mountain farm. In return, adopters are sent food products from the farm. The adoption scheme is inter-twined with an agri-tourism project which provides accommodation, runs a restaurant and engages in educational activities. The scheme is the result of the individual initiative of its founder, and is associated with a strongly expressed ethical position concerning the value of sustaining valued local rural landscapes and lifestyles, and the importance of 'reconnecting' urban dwellers with rural areas, farming and 'quality' food production. Yet the localness of the scheme is sustained through wider national and international networks: volunteer and paid workers are drawn from several European countries, funding has been acquired from the EU LEADER programme, and internet and transport technologies are essential in connecting with and supplying an international customer base. The broader economy of care instanced in this case study draws attention to a need to develop strategies for sustainable farmland management constructed around wider programmes of social, economic and cultural, as well as environmental, concern.  相似文献   
58.
There has been particular interest in 'alternative' food over the last 10 years, with many policymakers and researchers throughout the Minority World following a growing number of consumers and producers in supporting organic farming and a host of 'alternative' food networks. To date, there has been a tendency for theory and policy to emerge somewhat divorced from the grounded practices and experiences of producer-suppliers themselves within these networks. Urging a shift from 'alternativity' to 'sustainability' as a more critical and valuable tool to analyse food networks, this paper draws upon in-depth ethnographic research with small-scale producer-supplier case studies in south Wales and southern Ontario. In so doing it explores often overlooked voices and stories within sustainable food discourses. Focusing on the value of farmer-led understandings and responses, the paper highlights important implications for policymakers and consumers and outlines future research on sustainable food networks.  相似文献   
59.
基于可分解马尔科夫网的极端椒盐噪声图像滤波   总被引:4,自引:0,他引:4  
提出了一种基于可分解马尔科夫网(decomposableMarkovnetworks,DMN)的极端椒盐噪声的均值滤波方法,指出其网络节点的阈值衰减特性和网络节点的连接特性具有很好的对椒盐噪声污染图像的噪声定位的作用,并提出一种在该网络控制下,只对与噪声相关的像素进行均值计算以替代噪声像素的亚均值滤波算法,实现了图像的较强自适应滤波。实验表明,本文方法具有良好的滤波性能。  相似文献   
60.
地学自由曲面径向基函数网络重建的详细算法   总被引:3,自引:0,他引:3  
径向基函数(RadialBasisFunction,简称RBF)神经网络是一种理想的地学离散数据网格化工具,能够适应各种不同分布形式和边界条件的数据,收敛速度较快,可以逼近任何复杂曲面。这里详细介绍了RBF神经网络的算法。适当径向基函数的形式和偏差系数是使用RBF神经网络作地学曲面重建的关键。大量的实际数据验证结果表明,当选用Gauss型径向基函数时,一般可获得比较理想的网格化效果,同时具备"曲面平滑"和"拟合度高"的特点。  相似文献   
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