Heekyung Park

Heekyung Park

Korea Advanced Institute of Science and Technology

Professor

Department of Civil and Environmental Engineering

Research Area

  • #Computer science
  • #Materials science
  • #Environmental science
  • #Environmental engineering
  • #Environmental planning
  • #Genetic algorithm
  • #Artificial neural network
  • #Hazardous waste
  • #Water infrastructure
  • #Geography

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Contact information

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Related papers to
‘ Computer science ‘ : 3

  • Improving applicability of neuro-genetic algorithm to predict short-term water level: a case study

    2014/01

    1.4 Impact Factor

    6 citations

    Gooyong Lee, Sangeun Lee, Heekyung Park

    DOI : 10.2166/HYDRO.2013.011

    • #Computer science
    • #Artificial intelligence
    • #Machine learning
    • #Environmental engineering
    • #Artificial neural network
    • #Climate change
    • #Genetic algorithm
    • #River management
    • #Water level
    • #Adaptive capacity
    • #Artificial neural network model
    • #Water infrastructure

All papers authored by
‘ Heekyung Park ’ : 10

  • Sonocatalytic activity of a heterostructured β-Bi 2 O 3 /Bi 2 O 2 CO 3 nanoplate in degradation of bisphenol A

    2018/06
    ULTRASONICS SONOCHEMISTRY

    7.3 Impact Factor

    21 citations

    Gooyong Lee, Shaliza Ibrahim, Shanmuga Kittappa, Heekyung Park, Chang Min Park

    DOI : 10.1016/J.ULTSONCH.2018.02.015

    • #Materials science
    • #Nuclear chemistry
    • #Oxide
    • #Annealing (metallurgy)
    • #Irradiation
    • #Transmission electron microscopy
    • #X-ray photoelectron spectroscopy
    • #Bismuth
    • #Calcination
    • #Field emission microscopy

Related papers to
‘ Computer science ‘ : 3

  • Improving applicability of neuro-genetic algorithm to predict short-term water level: a case study

    2014/01
    JOURNAL OF HYDROINFORMATICS

    1.4 Impact Factor

    6 citations

    Gooyong Lee, Sangeun Lee, Heekyung Park

    DOI : 10.2166/HYDRO.2013.011

    • #Computer science
    • #Artificial intelligence
    • #Machine learning
    • #Environmental engineering
    • #Artificial neural network
    • #Climate change
    • #Genetic algorithm
    • #River management
    • #Water level
    • #Adaptive capacity
    • #Artificial neural network model
    • #Water infrastructure
  • Two-stage approach to quantify the resilience of maritime hazardous and noxious substance spill accidents

    2018/06
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION

    2.6 Impact Factor

    2 citations

    Eunlak Kim, Heekyung Park

    DOI : 10.1016/J.IJDRR.2018.01.009

    • #Computer science
    • #Environmental resource management
    • #Poison control
    • #Human factors and ergonomics
    • #Accident prevention
    • #Psychological resilience
    • #Port (computer networking)
    • #Hazardous waste
    • #Assessment methods
    • #Limited resources

Get access to
Contact information

Log in

All papers authored by
‘ Heekyung Park ’ : 10

  • Sonocatalytic activity of a heterostructured β-Bi 2 O 3 /Bi 2 O 2 CO 3 nanoplate in degradation of bisphenol A

    2018/06
    ULTRASONICS SONOCHEMISTRY

    7.3 Impact Factor

    21 citations

    Gooyong Lee, Shaliza Ibrahim, Shanmuga Kittappa, Heekyung Park, Chang Min Park

    DOI : 10.1016/J.ULTSONCH.2018.02.015

    • #Materials science
    • #Nuclear chemistry
    • #Oxide
    • #Annealing (metallurgy)
    • #Irradiation
    • #Transmission electron microscopy
    • #X-ray photoelectron spectroscopy
    • #Bismuth
    • #Calcination
    • #Field emission microscopy
  • Improving applicability of neuro-genetic algorithm to predict short-term water level: a case study

    2014/01
    JOURNAL OF HYDROINFORMATICS

    1.4 Impact Factor

    6 citations

    Gooyong Lee, Sangeun Lee, Heekyung Park

    DOI : 10.2166/HYDRO.2013.011

    • #Computer science
    • #Artificial intelligence
    • #Machine learning
    • #Environmental engineering
    • #Artificial neural network
    • #Climate change
    • #Genetic algorithm
    • #River management
    • #Water level
    • #Adaptive capacity
    • #Artificial neural network model
    • #Water infrastructure

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