scholarly journals Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty

2016 ◽  
Vol 52 (4) ◽  
pp. 2551-2570 ◽  
Author(s):  
Edom Moges ◽  
Yonas Demissie ◽  
Hong-Yi Li
Keyword(s):  
Hydrologic Model ◽  
Structural Uncertainty ◽  
Mixture Of Experts ◽  
Modeling Approach ◽  
Hierarchical Mixture Of Experts ◽  
Diagnostic Modeling

scholarly journals ASSESSING THE IMPACTS OF FLOODING CAUSED BY EXTREME RAINFALL EVENTS THROUGH A COMBINED GEOSPATIAL AND NUMERICAL MODELING APPROACH

2016 ◽  
Vol XLI-B8 ◽  
pp. 1271-1278
Author(s):  
J. R. Santillan ◽  
A. M. Amora ◽  
M. Makinano-Santillan ◽  
J. T. Marqueso ◽  
L. C. Cutamora ◽  
...  
Keyword(s):  
Land Cover ◽  
River Basin ◽  
Extreme Rainfall ◽  
Hydrologic Model ◽  
Extreme Rainfall Event ◽  
Hazard Maps ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Modeling Approach ◽  
Flood Depth

In this paper, we present a combined geospatial and two dimensional (2D) flood modeling approach to assess the impacts of flooding due to extreme rainfall events. We developed and implemented this approach to the Tago River Basin in the province of Surigao del Sur in Mindanao, Philippines, an area which suffered great damage due to flooding caused by Tropical Storms Lingling and Jangmi in the year 2014. The geospatial component of the approach involves extraction of several layers of information such as detailed topography/terrain, man-made features (buildings, roads, bridges) from 1-m spatial resolution LiDAR Digital Surface and Terrain Models (DTM/DSMs), and recent land-cover from Landsat 7 ETM+ and Landsat 8 OLI images. We then used these layers as inputs in developing a Hydrologic Engineering Center Hydrologic Modeling System (HEC HMS)-based hydrologic model, and a hydraulic model based on the 2D module of the latest version of HEC River Analysis System (RAS) to dynamically simulate and map the depth and extent of flooding due to extreme rainfall events. The extreme rainfall events used in the simulation represent 6 hypothetical rainfall events with return periods of 2, 5, 10, 25, 50, and 100 years. For each event, maximum flood depth maps were generated from the simulations, and these maps were further transformed into hazard maps by categorizing the flood depth into low, medium and high hazard levels. Using both the flood hazard maps and the layers of information extracted from remotely-sensed datasets in spatial overlay analysis, we were then able to estimate and assess the impacts of these flooding events to buildings, roads, bridges and landcover. Results of the assessments revealed increase in number of buildings, roads and bridges; and increase in areas of land-cover exposed to various flood hazards as rainfall events become more extreme. The wealth of information generated from the flood impact assessment using the approach can be very useful to the local government units and the concerned communities within Tago River Basin as an aid in determining in an advance manner all those infrastructures (buildings, roads and bridges) and land-cover that can be affected by different extreme rainfall event flood scenarios.

scholarly journals The Intelligent Control System for Biped Robot Using Hierarchical Mixture of Experts

2006 ◽  
Vol 16 (4) ◽  
pp. 389-395 ◽  
Author(s):  
Woo-Kyung Choi ◽  
Sang-Hyung Ha ◽  
Seong-Joo Kim ◽  
Yong-Taek Kim ◽  
Hong-Tae Jeon
Keyword(s):  
Control System ◽  
Intelligent Control ◽  
Biped Robot ◽  
Mixture Of Experts ◽  
Intelligent Control System ◽  
Hierarchical Mixture Of Experts

scholarly journals Dropout regularization in hierarchical mixture of experts

2021 ◽  
Vol 419 ◽  
pp. 148-156 ◽  
Author(s):  
Ozan İrsoy ◽  
Ethem Alpaydın
Keyword(s):  
Mixture Of Experts ◽  
Hierarchical Mixture Of Experts
Sign in / Sign up

Export Citation Format

Share Document