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Gunhui Chung

Researcher at University of Arizona

Publications -  27
Citations -  343

Gunhui Chung is an academic researcher from University of Arizona. The author has contributed to research in topics: Water supply & Water resources. The author has an hindex of 8, co-authored 25 publications receiving 294 citations. Previous affiliations of Gunhui Chung include Hoseo University & Korea University.

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Battle of the Water Calibration Networks

TL;DR: Calibration is a process of comparing model results with field data and making the appropriate adjustments so that both results agree as mentioned in this paper, which can involve formal optimization methods or manual methods in which the modeler informally examines alternative model parameters.
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Application of the Shuffled Frog Leaping Algorithm for the Optimization of a General Large-Scale Water Supply System

TL;DR: In this paper, a general large-scale water supply system model was developed to minimize the total system cost by integrating a mathematical supply system representation and applying an improved shuffled frog leaping algorithm optimization scheme (SFLA).
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Application of bivariate frequency analysis to the derivation of rainfall–frequency curves

TL;DR: In this paper, the Gumbel mixed model is used to construct rainfall-frequency curves at sample stations in Korea which provide joint relationships between amount, duration, and frequency of storm events.
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Optimal design of stormwater detention basin using the genetic algorithm

TL;DR: In this article, a stochastic search algorithm, a Genetic Algorithm (GA), is used to optimize the detention pond design, where the decision variables are the pond storage, and the pipe diameters and number of pipes for the service outlet.
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Applications of Network Analysis and Multi-objective Genetic Algorithm for Selecting Optimal Water Quality Sensor Locations in Water Distribution Networks

TL;DR: In this paper, the optimal water quality sensor placement is performed based on the sensitivity of flow direction under different water demands for detecting accidental water quality contamination in two water distribution networks using betweenness centrality (BC) and the Multi-Objective Genetic Algorithm (MOGA).