@article{ART001714781},
author={Gyeongyong Heo and 이창우 and Park Choong Shik},
title={Parameter Estimation in Debris Flow Deposition Model Using Pseudo Sample Neural Network},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2012},
volume={17},
number={11},
pages={11-18}
TY - JOUR
AU - Gyeongyong Heo
AU - 이창우
AU - Park Choong Shik
TI - Parameter Estimation in Debris Flow Deposition Model Using Pseudo Sample Neural Network
JO - Journal of The Korea Society of Computer and Information
PY - 2012
VL - 17
IS - 11
PB - The Korean Society Of Computer And Information
SP - 11
EP - 18
SN - 1598-849X
AB - Debris flow deposition model is a model to predict affected areas by debris flow and randomwalk model (RWM) was used to build themodel. Although themodel was proved to be effective in the prediction of affected areas, the model has several free parameters decided experimentally. There are several well-knownmethods to estimate parameters, however, they cannot be applied directly to the debris flowproblemdue to the small size of training data. In this paper, a modified neural network, called pseudo sample neural network (PSNN), was proposed to overcome the sample size problem. In the training phase, PSNNuses pseudo samples, which are generated using the existing samples. The pseudo samples smooth the solution space and reduce the probability of falling into a local optimum. As a result, PSNNcan estimate parameter more robustly than traditional neural networks do. All of these can be proved through the experiments using artificial and real data sets.
KW - Parameter Estimation;Pseudo Sample;Neural Network;Debris FlowDepositionModel
DO -
UR -
ER -
Gyeongyong Heo, 이창우 and Park Choong Shik. (2012). Parameter Estimation in Debris Flow Deposition Model Using Pseudo Sample Neural Network. Journal of The Korea Society of Computer and Information, 17(11), 11-18.
Gyeongyong Heo, 이창우 and Park Choong Shik. 2012, "Parameter Estimation in Debris Flow Deposition Model Using Pseudo Sample Neural Network", Journal of The Korea Society of Computer and Information, vol.17, no.11 pp.11-18.
Gyeongyong Heo, 이창우, Park Choong Shik "Parameter Estimation in Debris Flow Deposition Model Using Pseudo Sample Neural Network" Journal of The Korea Society of Computer and Information 17.11 pp.11-18 (2012) : 11.
Gyeongyong Heo, 이창우, Park Choong Shik. Parameter Estimation in Debris Flow Deposition Model Using Pseudo Sample Neural Network. 2012; 17(11), 11-18.
Gyeongyong Heo, 이창우 and Park Choong Shik. "Parameter Estimation in Debris Flow Deposition Model Using Pseudo Sample Neural Network" Journal of The Korea Society of Computer and Information 17, no.11 (2012) : 11-18.
Gyeongyong Heo; 이창우; Park Choong Shik. Parameter Estimation in Debris Flow Deposition Model Using Pseudo Sample Neural Network. Journal of The Korea Society of Computer and Information, 17(11), 11-18.
Gyeongyong Heo; 이창우; Park Choong Shik. Parameter Estimation in Debris Flow Deposition Model Using Pseudo Sample Neural Network. Journal of The Korea Society of Computer and Information. 2012; 17(11) 11-18.
Gyeongyong Heo, 이창우, Park Choong Shik. Parameter Estimation in Debris Flow Deposition Model Using Pseudo Sample Neural Network. 2012; 17(11), 11-18.
Gyeongyong Heo, 이창우 and Park Choong Shik. "Parameter Estimation in Debris Flow Deposition Model Using Pseudo Sample Neural Network" Journal of The Korea Society of Computer and Information 17, no.11 (2012) : 11-18.
