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Jeffrey Tim Query, Evaristo Diz
Pág. 145 - 159
AbstractIn this study we examine the robustness of fit for a multivariate and an autoregressive integrated moving average model to a data sample time series type. The sample is a recurrent actuarial data set for a 10-year horizon. We utilize ...
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António Carlos Pinheiro Fernandes, Luís Filipe Sanches Fernandes, Daniela Patrícia Salgado Terêncio, Rui Manuel Vitor Cortes and Fernando António Leal Pacheco
Interactions between pollution sources, water contamination, and ecological integrity are complex phenomena and hard to access. To comprehend this subject of study, it is crucial to use advanced statistical tools, which can unveil cause-effect relationsh...
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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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Stefano Alderighi, Paolo Landa, Elena Tànfani and Angela Testi
Molecular genetic techniques allow for the diagnosing of hereditary diseases and congenital abnormalities prenatally. A high variability of treatments exists, engendering an inappropriate clinical response, an inefficient use of resources, and the violat...
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Muge Pinar Komu, Hakan Ahmet Nefeslioglu and Candan Gokceoglu
Uncertainties related to runout distances in shallow landslide analyses may not only affect lives but may also result in economic losses. Owing to the increase in shallow landslides, which are especially triggered by heavy rainfall, runout distances have...
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Efrain Noa-Yarasca, Javier M. Osorio Leyton and Jay P. Angerer
Timely forecasting of aboveground vegetation biomass is crucial for effective management and ensuring food security. However, research on predicting aboveground biomass remains scarce. Artificial intelligence (AI) methods could bridge this research gap a...
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Liming Dong, Yuchao Lu, Guoqing Lei, Jiesheng Huang and Wenzhi Zeng
Intercropping radiation interception model is a promising tool for quantifying solar energy utilization in the intercropping system. However, few models have been proposed that can simulate intercropping radiation interception accurately and with simplic...
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Charalampos Skoulikaris
Large-scale hydrological modeling is an emerging approach in river hydrology, especially in regions with limited available data. This research focuses on evaluating the performance of two well-known large-scale hydrological models, namely E-HYPE and LISF...
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Julián Pulecio-Díaz, Miguel Sol-Sánchez and Fernando Moreno-Navarro
Roller-compacted concrete (RCC) pavements have been the subject of studies focused on their increasing deterioration over time due to the influence of vehicular loading and ambient factors in humidity and temperature conditions ranging from medium to low...
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