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Jae Young Seo and Sang-Il Lee
Drought is a complex phenomenon caused by lack of precipitation that affects water resources and human society. Groundwater drought is difficult to assess due to its complexity and the lack of spatio-temporal groundwater observations. In this study, we p...
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Shreyas Alagundi, T Palanisamy
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Marciel Lohmann,Leonardo José Cordeiro Santos
Alagamentos e inundações são fenômenos recorrentes principalmente nos meses de verão, cujas consequências acarretam diversos transtornos e perdas materiais para a população afetada. O presente artigo propõe determinar por meio de inteligência artificial ...
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Ahmed Skhiri, Ali Ferhi, Anis Bousselmi, Slaheddine Khlifi and Mohamed A. Mattar
A correct determination of irrigation water requirements necessitates an adequate estimation of reference evapotranspiration (ETo). In this study, monthly ETo is estimated using artificial neural network (ANN) models. Eleven combinations of long-term ave...
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Mark A. Denisenko, Alina S. Isaeva, Alexander S. Sinyukin and Andrey V. Kovalev
The fast, convenient, and accurate determination of railroad cars? load mass is critical to ensure safety and allow asset counting in railway infrastructure. In this paper, we propose a method for modeling the mechanical deformations that occur in the ra...
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Özhan Simsek
This study aimed to assess the susceptibility of three strawberry cultivars (?Festival?, ?Fortuna?, and ?Rubygem?) to drought stress induced by varying polyethylene glycol (PEG) concentrations in the culture medium. Plantlets were cultivated on a solid m...
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Angel E. Muñoz-Zavala, Jorge E. Macías-Díaz, Daniel Alba-Cuéllar and José A. Guerrero-Díaz-de-León
This paper reviews the application of artificial neural network (ANN) models to time series prediction tasks. We begin by briefly introducing some basic concepts and terms related to time series analysis, and by outlining some of the most popular ANN arc...
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Tomasz Gajewski and Pawel Skiba
The main goal of this work is to combine the usage of the numerical homogenization technique for determining the effective properties of representative volume elements with artificial neural networks. The effective properties are defined according to the...
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Dimitris Papadopoulos and Vangelis D. Karalis
Sample size is a key factor in bioequivalence and clinical trials. An appropriately large sample is necessary to gain valuable insights into a designated population. However, large sample sizes lead to increased human exposure, costs, and a longer time f...
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Jun Yeong Kim, Chang Geun Song, Jung Lee, Jong-Hyun Kim, Jong Wan Lee and Sun-Jeong Kim
In this paper, we propose a learning model for tracking the isolines of fluid based on the physical properties of particles in particle-based fluid simulations. Our method involves analyzing which weights, closely related to surface tracking among the va...
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