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Barbara Casentini, Marco Lazzazzara, Stefano Amalfitano, Rosamaria Salvatori, Daniela Guglietta, Daniele Passeri, Girolamo Belardi and Francesca Trapasso
The worldwide mining industry produces millions of tons of rock wastes, raising a considerable burden for managing both economic and environmental issues. The possible reuse of Fe/Mn-rich materials for arsenic removal in water filtration units, along wit...
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Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
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Héctor Andrés Melgar Sasieta, Fabiano Duarte Beppler, Roberto Carlos do Santos Pacheco (Author)
Pág. 381 - 389
This paper presents a model that aims to facilitate the visualization of the knowledge stored in digital repositories using visual archetypes. Archetypes are structures that contain visual representations of the real world that are known a priori by the ...
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Ziran Zhang and Maosheng Zhang
Describing the hydraulic conductivity of unsaturated soil is very important in predicting water transport. Most current models have complex forms and generally need to be calibrated by the measured unsaturated hydraulic conductivity curve. A simple model...
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Feifei He, Qinjuan Wan, Yongqiang Wang, Jiang Wu, Xiaoqi Zhang and Yu Feng
Accurately predicting hydrological runoff is crucial for water resource allocation and power station scheduling. However, there is no perfect model that can accurately predict future runoff. In this paper, a daily runoff prediction method with a seasonal...
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