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.

Characterization of daily rainfall variability in Hong Kong: A nonlinear dynamic perspective

Abstract: Department of Civil Engineering, University of Birmingham, Birmingham, UK Hong Kong Observatory, Kowloon, Hong Kong Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon, Hong Kong Joint Research Centre for Engineering Structure Disaster Prevention and Control, Guangzhou University, Guangzhou, China Key Laboratory of New Technology for Construction of Cities in Mountain Area, Ministry of Education, School of Civil Engineering, Chongqing University, Chongqing, China

Multiobjective Equivalent Static Wind Loads on Complex Tall Buildings Using Non-Gaussian Peak Factors

Abstract: Equivalent static wind loads (ESWLs) play an important role in the wind-resistant design of tall buildings. Traditionally, ESWLs of a tall building are derived based on the equivalence of the top deflection or the base force along the principal direction, which is easy to identify for a regular tall building. For flexible tall buildings with simple or complex shapes, wind-induced dynamic responses are three-dimensional, which often complicates the application of the ESWLs. Based on the time-domain dynamic analysis method, a new scheme is developed in this paper to model multiobjective equivalent static wind loads (M-ESWLs) on complex tall buildings. The possible non-Gaussian properties of wind-induced response processes have been taken into account in M-ESWLs by using non-Gaussian peak factors. Furthermore, a joint action reduction factor is carefully defined to reflect the partial correlations among multiple component responses. Finally, the new scheme is applied to a practical 43-story tall buil...

Full-Scale Measurements of Wind Pressures on a Low-Rise Building during Typhoons and Comparison with Wind Tunnel Test Results and Aerodynamic Database

Abstract: This study investigated wind-induced pressures on an instrumented low-rise building with gable roof and roof overhang during Typhoons Mujigae and Sarika by means of full-scale measurements....

I and i

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 …

Nonlinear Time Series Analysis.

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)