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2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)

作者： Zhou Li Chunxiang Li Department of Civil Engineering Shanghai University

ISBN: (纸本)9781510871076

Accurate forecasting of short term wind speed has been widely applied in the disaster early warning of civil *** the characteristics of non-stationary and nonlinear of wind speed,the actual wind speed time series need to be decomposed first and then *** this paper,a set of actual wind speed time series of typhoon is decomposed by four signal decomposing algorithms.(e.g.,Wavelet Packet Decomposition/Ensemble Empirical Mode Decomposition/Variational Mode Decomposition/Empirical Wavelet Transform) And the features of intrinsic mode functions from these four methods are fully ***,multi-step wind speed forecasting experiment based on least squares support vector machine optimized by bat algorithm is carried out to testify the effectiveness of the signal decomposing *** results of experiences indicate that the Empirical Wavelet Transform is effective in the wind speed accurate forecasting.

关键词： non-stationary wind speed four signal decomposing algorithms. bat algorithm decomposing algorithm

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A Study of Remote Sensing Image Landform Frame and Lithologic Component decomposing algorithm and Multifractal Feature of Rock Types

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Dixue Qianyuan/ Earth Science Frontiers 2009年第6期16卷 248-256页

作者： PAN, Wei NI, Guoqiang LI, Hanbo School of Optoelectronics Beijing Institute of Technology Beijing 100081 China National Key Laboratory of Remote Sensing Information and Image Analysis Technology Beijing Research Institute of Uranium Geology Beijing 100029 China

Landform frame-lithologic component decomposing algorithm for remote sensing (RS) image is proposed according to the principle of optical imaging and fractal feature of landform. The algorithm is applied to decompose the enhanced thematic mapper (ETM) image of rocks for the study of α-f(α) multifractal spectra. The original ETM image, decomposed landform frame and lithologic component subimage are used to calculate the α-f(α) multifractal spectra of adamellite and metamorphic sedimentary rocks in different areas. From the original ETM image, the α-f(α) multifractal spectra do not show any relation to rock types and landform. However, using the decomposed subimage, the adamellite from different areas shows the same α-f(α) spectra feature of the lithologic component subimage, but different α-f(α) spectra features of the landform frame subimage. On the contrary, the adamellite and metamorphic sedimentary rocks in the nearby area have different α-f(α) spectra of the lithologic component subimage, but rather similar α-f(α) spectra of the land frame subimage. This means the land frame-lithologic component algorithm and α-f(α) multifratal spectra can provide a new validated method to improve lithology recognition with RS image texture. © 2009 China University of Geosciences (Beijing) and Peking University.

关键词： α-f(α) multifractal spectra decomposing algorithm landform frame-lithologic component model remote sensing image rock types

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