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Xiaolu Li

Researcher at Beihang University

Publications -  124
Citations -  1520

Xiaolu Li is an academic researcher from Beihang University. The author has contributed to research in topics: Lidar & Ranging. The author has an hindex of 19, co-authored 110 publications receiving 977 citations. Previous affiliations of Xiaolu Li include Louisiana State University & University of Science and Technology of China.

Papers
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Measuring County Resilience After the 2008 Wenchuan Earthquake

TL;DR: Wen et al. as mentioned in this paper applied the resilience inference measurement (RIM) model to quantify and validate the community resilience of 105 counties in the impacted area, and applied discriminant analysis to quantify the influence of socioeconomic characteristics on the county's resilience.
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Comparative study of computational intelligence approaches for NOx reduction of coal-fired boiler

TL;DR: In this article, support vector regression (SVR) model based on CGA (Conventional Genetic Algorithm) was proposed to model the relationship between the operating parameters and the concentration of NOx emission.
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Deriving Bathymetry From Optical Images With a Localized Neural Network Algorithm

TL;DR: The experiments suggest that the LABPNN model is a viable solution to water depth retrieval from optical images, because of the better performance of neural networks than that of the regression models when the sample data are relatively sparse.
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Thermal modeling of CO2 in the injection well and reservoir at the Ordos CCS demonstration project, China

TL;DR: In this article, the authors developed a full-field model of a coupled injection well and reservoir to simulate the CO2 behavior during CO2 injection through the wellbore and reservoir, taking into account thermal exchanges with rocks and natural convection of water in the annulus.
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Temporal and Spatial Changes in Coupling and Coordinating Degree of New Urbanization and Ecological-Environmental Stress in China

TL;DR: Zhang et al. as discussed by the authors analyzed the spatial pattern and cluster mode of the coupling coordination of new urbanization and eco-environmental stress systems by using ArcGIS and GeoDa.