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421.
人工神经网络在煤层宏观结构解释中的应用 总被引:2,自引:2,他引:0
煤层中的宏观结构变化是我国众多煤田中普遍存在的地质现象,它对煤矿生产影响极大,是当前煤矿生产中急需解决的地质构造问题,利用工人神经网络可以解释煤层的分叉,合并及缺失等宏观结构问题,为矿井的采,掘工作的提供准确的地质资料。 相似文献
422.
423.
煤层含气量测井解释方法探讨 总被引:6,自引:1,他引:5
用多元线性回归建立煤层气含量与煤质参数、测井曲线值之间的回归方程,经F检验回归方程有效,但回归方程估算的煤层含气量与煤样解吸测定的含气量之间仍然存在较大的误差,为此利用BP神经网络进一步探讨它们之间的关系,实例表明预测精度较高。 相似文献
424.
At 31 sites in Finland the Zn content was determined of the epiphytic lichen Hypogymnia physodes (L.) Nyl. growing on pine and birch, the terricolous lichen Cladina spp. in pine bark, and the inner part of birch bark. The anomalous contents of Zn in H. physodes on pine and Cladina spp. in soil appeared to be strongly related to sulphide ore deposits. Anthropogenic Zn correlated closely with S and Fe in H. physodes on pine and with Fe in Cladina spp. The binding of geogenic Zn was related to iron hydroxides, and was attributed to the different uptake mechanism of S in these lichens. Elevated values of Zn in H. physodes on birch were due to both geogenic and anthropogenic sources. Zinc in pine bark increased with the Zn content in H. physodes and reached a limiting value. 相似文献
425.
426.
Improving neural network performance on the classification of complex geographic datasets 总被引:4,自引:0,他引:4
Neural Networks are now established computational tools used for search minimisation and data classification. They offer
some highly desirable features for landuse classification problems since they are able to take in a variety of data types,
recorded on different statistical scales, and combine them. As such, neural networks should offer advantages of increased
accuracy. However, a barrier to their general acceptance and use by all but `experts' is the difficulty of configuring the
network initially.
This paper describes the architectural problems of applying neural networks to landcover classification exercises in geography
and details some of the latest developments from an ongoing research project aimed at overcoming these problems. A comprehensive
strategy for the configuration of neural networks is presented, whereby the network is automatically constructed by a process
involving initial analysis of the training data. By careful study of the functioning of each part of the network it is possible
to select the architecture and initial weights on the node connections so the constructed network is `right first time'. Further
adaptations are described to control network behaviour, to optimise functioning from the perspective of landcover classification.
The entire configuration process is encapsulated by a single application which may be treated by the user as a `black box',
allowing the network to the applied in much the same way as a maximum likelihood classifier, with no further effort being
required of the user. 相似文献
427.
Simon Corne Tavi Murray Stan Openshaw Linda See Ian Turton 《Journal of Geographical Systems》1999,1(1):37-60
Measurements of water pressure beneath Trapridge Glacier, Yukon Territory, Canada show that the basal water system is highly
heterogeneous. Three types of behaviour were recorded: pressure records which are strongly correlated, records which are strongly
anticorrelated, and records which alternate between strong correlation and strong anticorrelation. We take the pressure in
bore-holes that are connected to the evacuation route for basal water as the forcing, and the other pressures as the response
to this forcing. Previous work (Murray and Clarke 1995) has shown that these relationships can be modelled using low-order
nonlinear differential equations optimized by inversion. However, despite optimizing the model parameters we cannot be sure that the final model forms are themselves optimal. Computational intelligence techniques provide alternative methods for fitting models and are robust
to missing or noisy data, applicable to non-smooth models, and attempt to derive optimal model forms as well as optimal model
parameters. Four computational intelligence techniques have been used and the results compared with the more conventional
mathematical model. These methods were genetic programming, artificial neural networks, fuzzy logic and self-organizing maps.
We compare each technique and offer an evaluation of their suitability for modelling the pressure data. The evaluation criteria
are threefold: (1) goodness of fit and an ability to predict subsequent data under different surface weather conditions; (2)
interpretability, and the extent and significance of any new insights offered into the physics of the glacier; (3) computation
time. The results suggest that the suitability of the computational intelligence techniques to model these data increases
with the complexity of the system to be modelled. 相似文献
428.
对确定三层BP网络隐层节点数的理论依据和现有做法进行了研究,提出了一种三层BP网络隐层节点数的双向确定法 相似文献
429.
用神经网络方法确定测区似大地水准面 总被引:3,自引:0,他引:3
本文提出一种用神经网络确定测区似大地水准面的方法,并给出了相应的神经网络结构和算法。研究了一个测区中用该方法确定的似大地水准面的精度,结果表明用该方法确定的似大地水准面的精度为厘米级,并与二次多项式曲面拟合似大地水准面的方法作了比较,神经网络方法的精度较优。 相似文献
430.