使用核平滑方法和人工神经网络模型的组合恢复地磁场的值

Q4 Earth and Planetary Sciences Geodeziya i Kartografiya Pub Date : 2023-01-20 DOI:10.22389/0016-7126-2022-990-12-57-64
O. Gvozdev, A. Materuhin, A. A. Maiorov
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引用次数: 0

摘要

本文描述了这项研究的结果,目的是在处理从高度移动的地理传感器网络接收的高强度时空数据流的基础上,改进解决地理场值恢复问题。此前,作者提出了一种解决这一任务的原始方法,即使用离散随机优化,特别是退火模拟方法,应用核函数自动确定的核平滑方法。作者提出的一种新方法的想法如下
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Restoring the values of geo-fields using a combination of kernel smoothing methods and artificial neural networks models
The purpose of the study, the results of which are described in the article, was to improve solving the matter of the geo-fields’ values restoring based on processing high-intensity spatial-temporal data streams received from a highly mobile geo-sensors network. Previously, the authors proposed an original approach to solving this task, which means applying the kernel smoothing methods, the nuclear function for which is determined automatically, using discrete stochastic optimization, in particular, the annealing simulation method. The idea of a new approach proposed by the authors is as follows
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来源期刊
Geodeziya i Kartografiya
Geodeziya i Kartografiya Earth and Planetary Sciences-Earth-Surface Processes
CiteScore
0.60
自引率
0.00%
发文量
73
期刊最新文献
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