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Julio Garrote, Ignacio Gutiérrez-Pérez and Andrés Díez-Herrero
Calibration and validation of flood risk maps at a national or a supra-national level remains a problematic aspect due to the limited information available to carry out these tasks. However, this validation is essential to define the representativeness o...
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Aleksy Kwilinski
Pág. 7 - 16
The article establishes that the development of an industrial enterprise in the conditions of the information economy requires an assessment of the competitiveness of the enterprise. To solve this problem, a mechanism for assessing the competitiveness of...
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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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Bahareh Kalantar, Husam A. H. Al-Najjar, Biswajeet Pradhan, Vahideh Saeidi, Alfian Abdul Halin, Naonori Ueda and Seyed Amir Naghibi
Assessment of the most appropriate groundwater conditioning factors (GCFs) is essential when performing analyses for groundwater potential mapping. For this reason, in this work, we look at three statistical factor analysis methods?Variance Inflation Fac...
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José Luis da Silva Pinho,António Pereira,Rolando Faria
Pág. 69 - 82
Os sistemas de previsão e alerta utilizados na gestão de recursos hídricos e operação de sistemas de drenagem tiveram desenvolvimentos significativos nos últimos anos. Esses desenvolvimentos resultaram da disponibilidade de informações meteorológicas em ...
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Guy Austern, Tanya Bloch and Yael Abulafia
The application of machine learning (ML) for the automatic classification of building elements is a powerful technique for ensuring information integrity in building information models (BIMs). Previous work has demonstrated the favorable performance of s...
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Sabrina De Nardi, Claudio Carnevale, Sara Raccagni and Lucia Sangiorgi
Models are a core element in performing local estimation of the climate change input. In this work, a novel approach to perform a fast downscaling of global temperature anomalies on a regional level is presented. The approach is based on a set of data-dr...
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Madhav Mukherjee, Ngoc Thuy Le, Yang-Wai Chow and Willy Susilo
As the demand for cybersecurity experts in the industry grows, we face a widening shortage of skilled professionals. This pressing concern has spurred extensive research within academia and national bodies, who are striving to bridge this skills gap thro...
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Alexander Robitzsch
Item response theory (IRT) models are frequently used to analyze multivariate categorical data from questionnaires or cognitive test data. In order to reduce the model complexity in item response models, regularized estimation is now widely applied, addi...
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Kenneth Thibodeau
Constructed Past Theory (CPT) is an abstract representation of how information about the past is produced and interpreted. It is grounded in the assertion that whatever we can write or say about anything in the past is the product of cognition. Understan...
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