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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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José Francisco Lima, Fernanda Catarina Pereira, Arminda Manuela Gonçalves and Marco Costa
Linear models, seasonal autoregressive integrated moving average (SARIMA) models, and state-space models have been widely adopted to model and forecast economic data. While modeling using linear models and SARIMA models is well established in the literat...
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Supraja Malladi and Qiqi Lu
The COVID-19 pandemic has had a catastrophic effect on the healthcare system including organ transplants worldwide. The number of living donor transplants performed in the US was affected more significantly by the pandemic with a 22.6% decrease in counts...
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Irina Kochetkova, Anna Kushchazli, Sofia Burtseva and Andrey Gorshenin
Fifth-generation (5G) networks require efficient radio resource management (RRM) which should dynamically adapt to the current network load and user needs. Monitoring and forecasting network performance requirements and metrics helps with this task. One ...
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Enna Hirata and Takuma Matsuda
With the increasing availability of large datasets and improvements in prediction algorithms, machine-learning-based techniques, particularly deep learning algorithms, are becoming increasingly popular. However, deep-learning algorithms have not been wid...
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Mohammed Achite, Ommolbanin Bazrafshan, Zahra Azhdari, Andrzej Walega, Nir Krakauer and Tommaso Caloiero
Water resources have always been a major concern, particularly in arid and semiarid parts of the world. Low precipitation and its uneven distribution in Algeria, along with fast population and agriculture activity increase and, particularly, recent droug...
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Marco Ferretti, Ugo Fiore, Francesca Perla, Marcello Risitano and Salvatore Scognamiglio
Accurate forecasts of containerised freight volumes are unquestionably important for port terminal operators to organise port operations and develop business plans. They are also relevant for port authorities, regulators, and governmental agencies dealin...
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Katleho Makatjane and Tshepiso Tsoku
This study aims to overcome the problem of dimensionality, accurate estimation, and forecasting Value-at-Risk (VaR) and Expected Shortfall (ES) uncertainty intervals in high frequency data. A Bayesian bootstrapping and backtest density forecasts, which a...
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Yuruixian Zhang, Wei Chong Choo, Jen Sim Ho and Cheong Kin Wan
Tourism forecasting has garnered considerable interest. However, integrating tourism forecasting with volatility is significantly less typical. This study investigates the performance of both the single models and their combinations for forecasting the v...
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Chaoli Tang, Dewei Hao, Yuanyuan Wei, Fangzheng Zhu, Xin Wu and Xiaomin Tian
To comprehensively explore the characteristics of global SST anomalies, a novel time?frequency combination method, based on the COBE data and NCEP/NCAR reanalysis products in the past 100 years, was developed. From the view of the time domain, the global...
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