Embedding machine learning techniques into a conceptual model to improve monthly runoff simulation: A nested hybrid rainfall-runoff modeling
One of the frequently adopted hybridizations within the scope of rainfall-runoff modeling
rests on directing various outputs simulated from the conceptual rainfall-runoff (CRR) …
rests on directing various outputs simulated from the conceptual rainfall-runoff (CRR) …
Prediction of unconfined compressive strength of carbonate rocks using artificial neural networks
N Ceryan, U Okkan, A Kesimal - Environmental earth sciences, 2013 - Springer
The unconfined compressive strength (UCS) of intact rocks is an important geotechnical
parameter for engineering applications. Determining UCS using standard laboratory tests is …
parameter for engineering applications. Determining UCS using standard laboratory tests is …
IoT-enabled flood severity prediction via ensemble machine learning models
River flooding is a natural phenomenon that can have a devastating effect on human life and
economic losses. There have been various approaches in studying river flooding; however …
economic losses. There have been various approaches in studying river flooding; however …
Investigating adaptive hedging policies for reservoir operation under climate change impacts
Concerns about whether the reservoirs against climate change will be able to fulfill their
missions in the future have revealed the necessity of adapting their operations to changing …
missions in the future have revealed the necessity of adapting their operations to changing …
A systematic review of predictor screening methods for downscaling of numerical climate models
Effective selection of climate predictors is a fundamental aspect of climate modeling
research. Predictor Screening (PS) plays a crucial role in identifying regional climate drivers …
research. Predictor Screening (PS) plays a crucial role in identifying regional climate drivers …
Prediction of daily streamflow using artificial neural networks (ANNs), wavelet neural networks (WNNs), and adaptive neuro-fuzzy inference system (ANFIS) models
HY Dalkiliç, SA Hashimi - Water Supply, 2020 - iwaponline.com
In recent years, the prediction of hydrological processes for the sustainable use of water
resources has been a focus of research by scientists in the field of hydrology and water …
resources has been a focus of research by scientists in the field of hydrology and water …
Reconstructing high resolution ESM data through a novel fast super resolution convolutional neural network (FSRCNN)
We present the first application of a fast super resolution convolutional neural network
(FSRCNN) based approach for downscaling earth system model (ESM) simulations. Unlike …
(FSRCNN) based approach for downscaling earth system model (ESM) simulations. Unlike …
Evaluation of the suitability of NCEP/NCAR, ERA-Interim and, ERA5 reanalysis data sets for statistical downscaling in the Eastern Black Sea Basin, Turkey
Climate community frequently uses gridded reanalysis data sets in their climate change
impact studies. However, these studies for a region yield more realistic results depending on …
impact studies. However, these studies for a region yield more realistic results depending on …
Estimation of prediction interval in ANN-based multi-GCMs downscaling of hydro-climatologic parameters
In this paper, point prediction and prediction intervals (PIs) of artificial neural network (ANN)
based downscaling for mean monthly precipitation and temperature of two stations (Tabriz …
based downscaling for mean monthly precipitation and temperature of two stations (Tabriz …
Application of support vector machines and relevance vector machines in predicting uniaxial compressive strength of volcanic rocks
N Ceryan - Journal of African Earth Sciences, 2014 - Elsevier
The uniaxial compressive strength (UCS) of intact rocks is an important and pertinent
property for characterizing a rock mass. It is known that standard UCS tests are destructive …
property for characterizing a rock mass. It is known that standard UCS tests are destructive …