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Kevin Mero, Nelson Salgado, Jaime Meza, Janeth Pacheco-Delgado and Sebastián Ventura
Unemployment, a significant economic and social challenge, triggers repercussions that affect individual workers and companies, generating a national economic impact. Forecasting the unemployment rate becomes essential for policymakers, allowing them to ...
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C. Tamilselvi, Md Yeasin, Ranjit Kumar Paul and Amrit Kumar Paul
Denoising is an integral part of the data pre-processing pipeline that often works in conjunction with model development for enhancing the quality of data, improving model accuracy, preventing overfitting, and contributing to the overall robustness of pr...
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Elena Pagano and Enrico Barbierato
Air pollution is a paramount issue, influenced by a combination of natural and anthropogenic sources, various diffusion modes, and profound repercussions for the environment and human health. Herein, the power of time series data becomes evident, as it p...
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Apostolos Ampountolas
This study analyzes the transmission of market uncertainty on key European financial markets and the cryptocurrency market over an extended period, encompassing the pre-, during, and post-pandemic periods. Daily financial market indices and price observa...
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Natalí Carbo-Bustinza, Hasnain Iftikhar, Marisol Belmonte, Rita Jaqueline Cabello-Torres, Alex Rubén Huamán De La Cruz and Javier Linkolk López-Gonzales
In the modern era, air pollution is one of the most harmful environmental issues on the local, regional, and global stages. Its negative impacts go far beyond ecosystems and the economy, harming human health and environmental sustainability. Given these ...
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Anastasios Kaltsounis, Evangelos Spiliotis and Vassilios Assimakopoulos
We present a machine learning approach for applying (multiple) temporal aggregation in time series forecasting settings. The method utilizes a classification model that can be used to either select the most appropriate temporal aggregation level for prod...
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Marco-Michael Temme, Olga Gluchshenko, Lennard Nöhren, Matthias Kleinert, Oliver Ohneiser, Kathleen Muth, Heiko Ehr, Niklas Groß, Annette Temme, Martina Lagasio, Massimo Milelli, Vincenzo Mazzarella, Antonio Parodi, Eugenio Realini, Stefano Federico, Rosa Claudia Torcasio, Markus Kerschbaum, Laura Esbrí, Maria Carmen Llasat, Tomeu Rigo and Riccardo Biondiadd Show full author list remove Hide full author list
In the H2020 project ?Satellite-borne and INsitu Observations to Predict The Initiation of Convection for ATM? (SINOPTICA), an air traffic controller support system was extended to organize approaching traffic even under severe weather conditions. During...
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Charalampos M. Liapis and Sotiris Kotsiantis
The use of deep learning in conjunction with models that extract emotion-related information from texts to predict financial time series is based on the assumption that what is said about a stock is correlated with the way that stock fluctuates. Given th...
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Luka Crnogorac, Suzana Lutovac, Rade Tokalic, Milo? Gligoric and Zoran Gligoric
Relatively large deformations of the steel arch support in underground coal mines in the Republic of Serbia present one of the main problems for achieving the planned production of coal. Monitoring of the critical sections of the steel arch support in th...
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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...
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