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Physical Sciences and Mathematics Commons™
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University of Nevada, Las Vegas
Civil and Environmental Engineering and Construction Faculty Research
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- Rayleigh waves (2)
- Artificial neural network (ANN) (1)
- Atlantic Multidecadal Oscillation (AMO) (1)
- El Nino–Southern Oscillations (ENSO) (1)
- Environmental engineering (1)
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- Geophysics (1)
- Long-range weather forecasting (1)
- Neural networks (Computer science) (1)
- North America – Colorado River Watershed (1)
- North Atlantic Oscillation (NAO) (1)
- Ocean-atmosphere interaction (1)
- Ocean-atmospheric oscillations (1)
- PDO (1)
- Seismology--Analysis (1)
- Shear waves (1)
- Streamflow – Forecasting (1)
- Support Vector Machines (SVM) (1)
- Surface waves--Measurement (1)
Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Using Oceanic-Atmospheric Oscillations For Long Lead Time Streamflow Forecasting, Ajay Kalra, Sajjad Ahmad
Using Oceanic-Atmospheric Oscillations For Long Lead Time Streamflow Forecasting, Ajay Kalra, Sajjad Ahmad
Civil and Environmental Engineering and Construction Faculty Research
We present a data-driven model, Support Vector Machine (SVM), for long lead time streamflow forecasting using oceanic-atmospheric oscillations. The SVM is based on statistical learning theory that uses a hypothesis space of linear functions based on Kernel approach and has been used to predict a quantity forward in time on the basis of training from past data. The strength of SVM lies in minimizing the empirical classification error and maximizing the geometric margin by solving inverse problem. The SVM model is applied to three gages, i.e., Cisco, Green River, and Lees Ferry in the Upper Colorado River Basin in the …
Role Of Forward Model In Surface-Wave Studies To Delineate A Buried High-Velocity Layer, Xiaohui Jin, Barbara Luke, Carlos Calderon-Macias
Role Of Forward Model In Surface-Wave Studies To Delineate A Buried High-Velocity Layer, Xiaohui Jin, Barbara Luke, Carlos Calderon-Macias
Civil and Environmental Engineering and Construction Faculty Research
Procedures are tested and compared for processing Rayleigh surface wave data to obtain one-dimensional shear wave velocity profiles for a hypothetical site that contains a buried high-velocity layer (HVL). The main purpose of such an investigation would be to discriminate and characterize the HVL. When target dispersion curves are derived from synthetic time histories, for the most part, the HVL is better identified when profiles are inverted using only the fundamental mode of Rayleigh wave propagation, rather than a more compatible but more complex forward model. The outcomes imply that in practice, a simple forward model might be more successful …
Interpreting Surface-Wave Data For A Site With Shallow Bedrock, Daniel W. Casto, Barbara Luke, Carlos Calderon-Macias, Ronald Kaufmann
Interpreting Surface-Wave Data For A Site With Shallow Bedrock, Daniel W. Casto, Barbara Luke, Carlos Calderon-Macias, Ronald Kaufmann
Civil and Environmental Engineering and Construction Faculty Research
The inversion of dispersive Rayleigh-wave data has been shown to be successful in providing reliable estimated shear-wave velocities within unconsolidated materials in the near surface. However, in a case where the multi-channel analysis of surface waves method was applied to a site consisting of clay residuum overlying basalt bedrock, inversion for the fundamental-mode Rayleigh wave resulted in shear-wave velocities within the rock that are less than half of expected values. Forward modeling reveals that the fundamental-mode dispersion curve is hardly sensitive to bedrock velocity perturbations over a practical range of wavelengths, leading to poorly constrained solutions. Standard surface-wave methods can …