Comparison of three recurrent neural networks for rainfall-runoff modelling at a snow-dominated watershed

Date

2021-10-25

Author

Yokoo, K.
Ishida, K.
Nagasato, T.
Ercan, Ali
Tu, T.

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

51
views

0
downloads

© Published under licence by IOP Publishing Ltd.In recent years, rainfall-runoff modelling using LSTM has shown high adaptability. However, LSTM requires far more computational costs than traditional RNN. In addition, a different type of RNN, GRU, has been developed to solve this issue of LSTM. Therefore, this study compares the accuracy of the deep learning methods for rainfall-runoff modelling using three deep learning methods in a snow-dominated area. Besides, the setting of hyperparameters may affect accuracy. The accuracy of these deep learning methods was investigated by trying multiple combinations of hyperparameters. The input data were daily temperature data and precipitation data. The results show that GRU gives the highest accuracy in most combinations.

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85118956686&origin=inward
https://hdl.handle.net/11511/100716

DOI

https://doi.org/10.1088/1755-1315/851/1/012012

Conference Name

2021 International Conference on Geological Engineering and Geosciences, ICGoES 2021

Collections

Department of Civil Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Comparison of Prognostic and Diagnostic Approaches to Modeling Evapotranspiration in the Nile River Basin Yılmaz, Mustafa Tuğrul; Zaitchik, Benjamin F; Crow, Wt; Hain, Christopher; Ozdogan, Mutlu; Chun, Jong A (2012-12-03) Actual evapotranspiration (ET) can be estimated using both prognostic and diagnostic modeling approaches, providing independent yet complementary information for hydrologic applications. Both approaches have advantages and disadvantages. When provided with temporally continuous atmospheric forcing data, prognostic models offer continuous sub-daily ET information together with the full set of water and energy balance fluxes and states (i.e. soil moisture, runoff, sensible and latent heat). On the other hand,...
Comparison of 2D and 3D image-based aggregate morphological indices Kutay, M. Emin; Öztürk, Hande Işık; Abbas, Ala R.; Hu, Chichun (2011-01-01) Significant progress has been made over the last two decades in the characterisation of aggregate shape using automated image analysis and processing methods. Aggregate shape characteristics have been quantified using three distinct shape parameters, namely the aggregate form, angularity and surface texture. Several mathematical procedures have been developed to quantify these parameters. For practical reasons, most of these procedures were limited to two-dimensional (2D) and utilised 2D aggregate images. T...
Exploitation of multi-camera configurations for visual surveillance Akman, Oytun; Alatan, Abdullah Aydın; Çiloğlu, Tolga (2008-06-20) In this paper, we propose novel methods for background modeling, occlusion. handling and event recognition by using multi-camera configurations. Homography-related positions are utilized to construct a mixture of multivariate Gaussians to generate a background model for each pixel of the reference camera. Occlusion handling is achieved by generation of the top-view via trifocal tensors, as a result of matching over-segmented regions instead of pixels. The resulting graph is segmented into objects after dete...
Analysis and control of a running spring-mass model with a trunk based on virtual pendulum concept Karagoz, O K; Secer, G; Ankaralı, Mustafa Mert; Saranli, U (2022-05-26) © 2022 IOP Publishing Ltd.The spring-loaded inverted pendulum model has been one of the most studied conceptual models in the locomotion community. Even though it can adequately explain the center of mass trajectories of numerous legged animals, it remains insufficient in template-based control of complex robot platforms, being unable to capture additional dynamic characteristics of locomotion exhibited in additional degrees of freedom such as trunk pitch oscillations. In fact, analysis of trunk behavior du...
Comparison of HK and SC Curvature Descriptions in a Scale-Space for the Purpose of 3D Object Recognition Akagündüz, Erdem; Ulusoy, İlkay (2009-01-01) Most 3D object recognition methods use mean-Gaussian curvatures (HK) [2] or shape index-curvedness (SC) [3] values for classification. Although these two curvature descriptions classify objects into same categories, their mathematical definitions vary. In this study a comparion between the two curvature description is carried out for the purpose of 3D object recognition. Since unlike S; H, K and C values are not invariant of scale and resolution, a method to set them fully invariant to any transforation is ...

Citation Formats

K. Yokoo, K. Ishida, T. Nagasato, A. Ercan, and T. Tu, “Comparison of three recurrent neural networks for rainfall-runoff modelling at a snow-dominated watershed,” Yogyakarta, Virtual, Endonezya, 2021, vol. 851, Accessed: 00, 2022. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85118956686&origin=inward.