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Qiusheng Li

Bio: Qiusheng Li is an academic researcher from City University of Hong Kong. The author has contributed to research in topics: Wind speed & Wind tunnel. The author has an hindex of 47, co-authored 429 publications receiving 8830 citations. Previous affiliations of Qiusheng Li include Chinese Ministry of Education & Guangzhou University.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the exact solutions for the stability analysis of a one-step bar of varying cross-section subjected to concentrated and distributed axial loads are found first, and then the exact solution of that bar is used to derive the eigenvalue equation of a multi-stage bar of different cross-sections subjected to more complicated loads by using transition matrices.

48 citations

Journal ArticleDOI
TL;DR: In this paper, a modified independent modal space control (MIMSC) algorithm is proposed to eliminate the effect of modal control force on the uncontrolled modes, which is more effective than IMSC.

46 citations

Journal ArticleDOI
TL;DR: In this paper, a simple empirical model with improved accuracy for 3D axisymmetric steady-state velocity fields of downbursts and impinging jets is proposed. But the model is not suitable for the downburst wind characteristics.

46 citations

Journal ArticleDOI
TL;DR: In this article, a transfer matrix method was used to analyze the free vibration and the forced vibration of a pipe system with multi-pipe sections subjected to various kinds of external excitations.

45 citations

Journal ArticleDOI
TL;DR: In this article, a new dynamic model based on the shell theory is presented to investigate the vibration behavior of a rotating composite laminated blade with a pre-twisted angle, where the effects of the Coriolis and centrifugal forces due to the rotation motion of the blade are considered in the formulation.

45 citations


Cited by
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Journal ArticleDOI

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08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Book ChapterDOI
11 Dec 2012

1,704 citations

Journal ArticleDOI

1,604 citations

01 Mar 1995
TL;DR: This thesis applies neural network feature selection techniques to multivariate time series data to improve prediction of a target time series and results indicate that the Stochastics and RSI indicators result in better prediction results than the moving averages.
Abstract: : This thesis applies neural network feature selection techniques to multivariate time series data to improve prediction of a target time series. Two approaches to feature selection are used. First, a subset enumeration method is used to determine which financial indicators are most useful for aiding in prediction of the S&P 500 futures daily price. The candidate indicators evaluated include RSI, Stochastics and several moving averages. Results indicate that the Stochastics and RSI indicators result in better prediction results than the moving averages. The second approach to feature selection is calculation of individual saliency metrics. A new decision boundary-based individual saliency metric, and a classifier independent saliency metric are developed and tested. Ruck's saliency metric, the decision boundary based saliency metric, and the classifier independent saliency metric are compared for a data set consisting of the RSI and Stochastics indicators as well as delayed closing price values. The decision based metric and the Ruck metric results are similar, but the classifier independent metric agrees with neither of the other metrics. The nine most salient features, determined by the decision boundary based metric, are used to train a neural network and the results are presented and compared to other published results. (AN)

1,545 citations