Chih‐Yu Liu
Biographic Data
| ID | 7868465 |
|---|---|
| NAME | Chih‐Yu Liu |
| GIVEN NAMES | Chih‐Yu |
| FAMILY NAME | Liu |
| SIGNATURE | LIU C Y |
| AFFILIATIONS | National Taiwan Ocean University |
| ORCID | 0000-0002-2018-3401 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2007 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 0 |
A GIS-Based Artificial Neural Network Model for Flood Susceptibility Assessment
This article presents a geographic information system (GIS)-based artificial neural network (GANN) model for flood susceptibility assessment of Keelung City, Taiwan. Various factors, including elevation, slope angle, slope aspect, flow accumulation, flow direction, topographic wetness index (TWI), drainage density, rainfall, and normalized difference vegetation index, were generated using a digital elevation model and LANDSAT 8 imagery. Historica…
Formulation and Application of the Generalized Multilevel Facets Model
In this study, the authors develop a generalized multilevel facets model, which is not only a multilevel and two-parameter generalization of the facets model, but also a multilevel and facet generalization of the generalized partial credit model. Because the new model is formulated within a framework of nonlinear mixed models, no efforts are needed to develop parameter estimation procedures, and existing computer programs can be directly applied.…
No prominent works on this page.
Formulation and Application of the Generalized Multilevel Facets Model
In this study, the authors develop a generalized multilevel facets model, which is not only a multilevel and two-parameter generalization of the facets model, but also a multilevel and facet generalization of the generalized partial credit model. Because the new model is formulated within a framework of nonlinear mixed models, no efforts are needed to develop parameter estimation procedures, and existing computer programs can be directly applied.…
A GIS-Based Artificial Neural Network Model for Flood Susceptibility Assessment
This article presents a geographic information system (GIS)-based artificial neural network (GANN) model for flood susceptibility assessment of Keelung City, Taiwan. Various factors, including elevation, slope angle, slope aspect, flow accumulation, flow direction, topographic wetness index (TWI), drainage density, rainfall, and normalized difference vegetation index, were generated using a digital elevation model and LANDSAT 8 imagery. Historica…
Computer Science (2 works) · Mathematics (2 works) · Applied Mathematics (1 works) · Applied Mathematics (1 works) · Artificial neural network (1 works) · Data mining (1 works) · Digital elevation model (1 works) · Elevation (ballistics (1 works) · Environmental Science (1 works) · Facet (psychology) (1 works)