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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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Krzysztof Drachal and Michal Pawlowski
This study firstly applied a Bayesian symbolic regression (BSR) to the forecasting of numerous commodities? prices (spot-based ones). Moreover, some features and an initial specification of the parameters of the BSR were analysed. The conventional approa...
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Yongqi Liu, Guibing Hou, Baohua Wang, Yang Xu, Rui Tian, Tao Wang and Hui Qin
Flood control operation of cascade reservoirs is an important technology to reduce flood disasters and increase economic benefits. Flood forecast information can help reservoir managers make better use of flood resources and reduce flood risks. In this p...
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Ru Wang, Qingyu Zheng, Wei Li, Guijun Han, Xuan Wang and Song Hu
The uncertainty in the initial condition seriously affects the forecasting skill of numerical models. Targeted observations play an important role in reducing uncertainty in numerical prediction. The conditional nonlinear optimal perturbation (CNOP) meth...
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Juan Nunez-Portillo, Alfonso Valenzuela, Antonio Franco and Damián Rivas
This paper presents an approach for integrating uncertainty information in air traffic flow management at the tactical phase. In particular, probabilistic methodologies to predict sector demand and sector congestion under adverse weather in a time horizo...
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Xiaoou Li
This paper tackles the challenge of time series forecasting in the presence of missing data. Traditional methods often struggle with such data, which leads to inaccurate predictions. We propose a novel framework that combines the strengths of Generative ...
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Luis Zuloaga-Rotta, Rubén Borja-Rosales, Mirko Jerber Rodríguez Mallma, David Mauricio and Nelson Maculan
The forecasting of presidential election results (PERs) is a very complex problem due to the diversity of electoral factors and the uncertainty involved. The use of a hybrid approach composed of techniques such as machine learning (ML) and Simulation in ...
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Han Lin Shang
A key summary statistic in a stationary functional time series is the long-run covariance function that measures serial dependence. It can be consistently estimated via a kernel sandwich estimator, which is the core of dynamic functional principal compon...
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Francisca Lanai Ribeiro Torres, Luana Medeiros Marangon Lima, Michelle Simões Reboita, Anderson Rodrigo de Queiroz and José Wanderley Marangon Lima
Streamflow forecasting plays a crucial role in the operational planning of hydro-dominant power systems, providing valuable insights into future water inflows to reservoirs and hydropower plants. It relies on complex mathematical models, which, despite t...
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Chenkai Cai, Yi?an Hua, Huibin Yang, Jing Wang, Changhuai Wu, Helong Wang and Xinyi Shen
Ecological droughts in rivers, as a new type of drought, have been greatly discussed in the past decade. Although various studies have been conducted to identify and evaluate ecological droughts in rivers from different indices, a forecast model for this...
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