Zobrazeno 1 - 10
of 247
pro vyhledávání: '"Ercan, Ali"'
Autor:
Nagasato, Takeyoshi, Ishida, Kei, Ercan, Ali, Tu, Tongbi, Kiyama, Masato, Amagasaki, Motoki, Yokoo, Kazuki
Deep learning has been utilized for the statistical downscaling of climate data. Specifically, a two-dimensional (2D) convolutional neural network (CNN) has been successfully applied to precipitation estimation. This study implements a three-dimensio
Externí odkaz:
http://arxiv.org/abs/2112.06571
An architecture consisting of a serial coupling of the one-dimensional convolutional neural network (1D-CNN) and the long short-term memory (LSTM) network, which is referred as CNNsLSTM, was proposed for hourly-scale rainfall-runoff modeling in this
Externí odkaz:
http://arxiv.org/abs/2111.04732
Autor:
Yokoo, Kazuki, Ishida, Kei, Ercan, Ali, Tu, Tongbi, Nagasato, Takeyoshi, Kiyama, Masato, Amagasaki, Motoki
This study investigates the relationships which deep learning methods can identify between the input and output data. As a case study, rainfall-runoff modeling in a snow-dominated watershed by means of a long- and short-term memory (LSTM) network is
Externí odkaz:
http://arxiv.org/abs/2106.07963
Publikováno v:
In Journal of Environmental Management May 2024 359
This study proposes two straightforward yet effective approaches to reduce the required computational time of the training process for time-series modeling through a recurrent neural network (RNN) using multi-time-scale time-series data as input. One
Externí odkaz:
http://arxiv.org/abs/2103.10932
Publikováno v:
In Journal of Hydrology: Regional Studies October 2021 37
Autor:
Ercan, Ali1 ali.ercan@ogr.iu.edu.tr, Gülboy, Burak Samih2 bsg@istanbul.edu.tr
Publikováno v:
Journal of Applied & Theoretical Social Sciences. Mar2023, Vol. 5 Issue 1, p1-18. 18p.
Autor:
Ercan, Ali Ozer.
Publikováno v:
May be available electronically.
Thesis (Ph. D.)--Stanford University, 2007.
Submitted to the Department of Electrical Engineering. Copyright by the author.
Submitted to the Department of Electrical Engineering. Copyright by the author.
Publikováno v:
In Journal of Hydrology January 2020 580