G
Guohe Huang
Researcher at Applied Science Private University
Publications - 1071
Citations - 30520
Guohe Huang is an academic researcher from Applied Science Private University. The author has contributed to research in topics: Stochastic programming & Fuzzy logic. The author has an hindex of 72, co-authored 979 publications receiving 25589 citations. Previous affiliations of Guohe Huang include Peking University & Beijing Normal University.
Papers
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Development of an artificial neural network model for predicting minimum miscibility pressure in CO2 flooding
TL;DR: In this article, the authors presented the development of an artificial neural network (ANN) model for the prediction of pure and impure CO 2 minimum miscibility pressures (MMP) of oils.
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Newly designed primer pair revealed dominant and diverse comammox amoA gene in full-scale wastewater treatment plants.
TL;DR: New dimension and fundamental basis for future researches towards biogeochemical nitrogen cycle is provided and qPCR results demonstrated a remarkably high abundance of CAOB amoA gene, which were up to 182.7-fold more abundant than AOB amiA gene.
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Grey quadratic programming and its application to municipal solid waste management planning under uncertainty
TL;DR: In this article, a grey quadratic programming (GQP) method is proposed for decision making under uncertainty, which improves upon existing grey linear programming (GLP) by allowing the consideration of the effects of economies of scale on cost coefficients in the objective function.
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An inexact two-stage water management model for planning agricultural irrigation under uncertainty
TL;DR: Targeted incomes, recourse costs, and net system benefits under different scenarios are analyzed, which indicates that different policies for agricultural irrigation targets correspond to different water shortages and surplus, and thus lead to varied system benefit and system-failure risk.
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Energy and environmental systems planning under uncertainty—an inexact fuzzy-stochastic programming approach
TL;DR: In this paper, an inexact fuzzy-stochastic energy model (IFS-EM) is developed for planning energy and environmental systems (EES) management under multiple uncertainties.