|
|
|
Manuel Zamudio López, Hamidreza Zareipour and Mike Quashie
This research proposes an investigative experiment employing binary classification for short-term electricity price spike forecasting. Numerical definitions for price spikes are derived from economic and statistical thresholds. The predictive task employ...
ver más
|
|
|
|
|
|
|
Shih-Lun Fang, Yi-Shan Lin, Sheng-Chih Chang, Yi-Lung Chang, Bing-Yun Tsai and Bo-Jein Kuo
The reference evapotranspiration (ET0) information is crucial for irrigation planning and water resource management. While the Penman-Monteith (PM) equation is widely recognized for ET0 calculation, its reliance on numerous meteorological parameters cons...
ver más
|
|
|
|
|
|
|
Yuxiu Liu, Xing Yuan, Yang Jiao, Peng Ji, Chaoqun Li and Xindai An
Integrating numerical weather forecasts that provide ensemble precipitation forecasts, land surface hydrological modeling that resolves surface and subsurface hydrological processes, and artificial intelligence techniques that correct the forecast bias, ...
ver más
|
|
|
|
|
|
|
Louis Closson, Christophe Cérin, Didier Donsez and Jean-Luc Baudouin
This paper aims to provide discernment toward establishing a general framework, dedicated to data analysis and forecasting in smart buildings. It constitutes an industrial return of experience from an industrialist specializing in IoT supported by the ac...
ver más
|
|
|
|
|
|
|
Fahim Sufi
In the face of escalating cyber threats that have contributed significantly to global economic losses, this study presents a comprehensive dataset capturing the multifaceted nature of cyber-attacks across 225 countries over a 14-month period from October...
ver más
|
|
|
|
|
|
|
Wei He and Mingze Chen
The advancement of cutting-edge technologies significantly transforms urban lifestyles and is indispensable in sustainable urban design and planning. This systematic review focuses on the critical role of innovative technologies and digitalization, parti...
ver más
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
Konstantinos P. Fourkiotis and Athanasios Tsadiras
In today?s evolving global world, the pharmaceutical sector faces an emerging challenge, which is the rapid surge of the global population and the consequent growth in drug production demands. Recognizing this, our study explores the urgent need to stren...
ver más
|
|
|
|
|
|
|
Theofani Psomouli, Ioannis Kansizoglou and Antonios Gasteratos
The increase in the concentration of geological gas emissions in the atmosphere and particularly the increase of methane is considered by the majority of the scientific community as the main cause of global climate change. The main reasons that place met...
ver más
|
|
|
|
|
|
|
Vaia I. Kontopoulou, Athanasios D. Panagopoulos, Ioannis Kakkos and George K. Matsopoulos
In the broad scientific field of time series forecasting, the ARIMA models and their variants have been widely applied for half a century now due to their mathematical simplicity and flexibility in application. However, with the recent advances in the de...
ver más
|
|
|
|