Cited by
Cited by
Application of neural networks for estimation of concrete strength
JI Kim, DK Kim, MQ Feng, F Yazdani
Journal of Materials in Civil Engineering 16 (3), 257-264, 2004
Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models
RC Deo, P Samui, D Kim
Stochastic Environmental Research and Risk Assessment 30, 1769-1784, 2016
Baseline models for bridge performance monitoring
MQ Feng, DK Kim, JH Yi, Y Chen
Journal of Engineering Mechanics 130 (5), 562-569, 2004
Application of probabilistic neural networks for prediction of concrete strength
DK Kim, JJ Lee, JH Lee, SK Chang
Journal of Materials in Civil Engineering 17 (3), 353-362, 2005
Modelling the energy performance of residential buildings using advanced computational frameworks based on RVM, GMDH, ANFIS-BBO and ANFIS-IPSO
N Kardani, A Bardhan, D Kim, P Samui, A Zhou
Journal of Building Engineering 35, 102105, 2021
Multiple tuned mass damper for multi-mode vibration reduction of offshore wind turbine under seismic excitation
M Hussan, MS Rahman, F Sharmin, D Kim, J Do
Ocean Engineering 160, 449-460, 2018
Time‐domain soil–structure interaction analysis in two‐dimensional medium based on analytical frequency‐dependent infinite elements
DK Kim, CB Yun
International Journal for Numerical Methods in Engineering 47 (7), 1241-1261, 2000
Analytical frequency-dependent infinite elements for soil–structure interaction analysis in two-dimensional medium
CB Yun, DK Kim, JM Kim
Engineering structures 22 (3), 258-271, 2000
Prediction of compressive strength of self-compacting concrete using least square support vector machine and relevance vector machine
BG Aiyer, D Kim, N Karingattikkal, P Samui, PR Rao
KSCE Journal of Civil Engineering 18, 1753-1758, 2014
Modeling of nonlinear cyclic load behavior of I-shaped composite steel-concrete shear walls of nuclear power plants
A Ali, D Kim, SG Cho
Nuclear Engineering and Technology 45 (1), 89-98, 2013
Structural dynamics
DG Kim
Comparison of machine learning techniques to predict compressive strength of concrete
S Dutta, P Samui, D Kim
Comput. Concr 21 (4), 463-470, 2018
Hybrid wireless smart sensor network for full-scale structural health monitoring of a cable-stayed bridge
H Jo, SH Sim, KA Mechitov, R Kim, J Li, P Moinzadeh, BF Spencer Jr, ...
Sensors and Smart Structures Technologies for Civil, Mechanical, and …, 2011
Damping effects of the passive control devices on structural vibration control: TMD, TLC and TLCD for varying total masses
Y Bigdeli, D Kim
KSCE Journal of Civil Engineering 20, 301-308, 2016
Utilization relevance vector machine for slope reliability analysis
P Samui, T Lansivaara, D Kim
Applied Soft Computing 11 (5), 4036-4040, 2011
Uplift capacity of suction caisson in clay using multivariate adaptive regression spline
P Samui, S Das, D Kim
Ocean Engineering 38 (17-18), 2123-2127, 2011
An improved application technique of the adaptive probabilistic neural network for predicting concrete strength
JJ Lee, D Kim, SK Chang, CFM Nocete
Computational Materials Science 44 (3), 988-998, 2009
AHP-based evaluation model for optimal selection process of patching materials for concrete repair: focused on quantitative requirements
JY Do, DK Kim
International Journal of Concrete Structures and Materials 6, 87-100, 2012
GPS-structural health monitoring of a long span bridge using neural network adaptive filter
MR Kaloop, D Kim
Survey Review 46 (334), 7-14, 2014
Nonlinear seismic soil-structure interaction analysis of nuclear reactor building considering the effect of earthquake frequency content
D Van Nguyen, D Kim, DD Nguyen
Structures 26, 901-914, 2020
The system can't perform the operation now. Try again later.
Articles 1–20