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Zhou Wei-hong

Researcher at Chinese Academy of Sciences

Publications -  5
Citations -  34

Zhou Wei-hong is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Short-time Fourier transform & Stellar classification. The author has an hindex of 2, co-authored 5 publications receiving 28 citations. Previous affiliations of Zhou Wei-hong include Minzu University of China.

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Journal ArticleDOI

Determination of isoniazid and hydrazine by capillary electrophoresis with amperometric detection at a Pt‐particle modified carbon fiber microelectrode

TL;DR: Capillary electrophoresis (CE)/electrochemical detection (EC) for the simultaneous determination of hydrazine and isoniazid has been developed as mentioned in this paper, which uses a novel modified electrode dispersed with ultrafine platinum particles on the surface of a 30 mu m carbon fiber microelectrode.
Proceedings ArticleDOI

A fuzzy classifier based on Mamdani fuzzy logic system and genetic algorithm

TL;DR: A new way of creating Mamdani fuzzy classifier based on MAMDani fuzzy logical system is proposed in this paper, and the new fuzzy classifiers is improved with the genetic algorithm further.
Journal ArticleDOI

A New Stellar Spectral Feature Extraction Method Based on Two-dimensional Fourier Spectrum Image and Its Application in the Stellar Spectral Classification Based on Deep Network

TL;DR: This paper proposes a new feature extraction method for astronomical spectra based on two-dimensional Fourier spectrum image, and applies the method to the classification study of LAMOST stellar spectral data.
Journal ArticleDOI

Stellar Spectral Classification Based on Capsule Network

TL;DR: Zhang et al. as discussed by the authors proposed a capsule network for stellar spectral classification using one-dimensional convolutional network and short-time Fourier transform (STFT) to preserve the hierarchical pose relationships among the entities in the image.
Proceedings ArticleDOI

A new hybrid genetic algorithm based on clan competition

TL;DR: It is proved that the probability of the new hybrid genetic algorithm convegent to the global optimal solution is 1, and it is illustrated that the new algorithm is the robustest among the three algorithms, what's more, it has the highest precision with the equal parameters.