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Forecasting, Volume 6, Issue 2

2024 June - 13 articles

Cover Story: Convective storms are dangerous weather phenomena that can cause heavy rainfalls. Predicting them is difficult due to their high speed and variability, but essential to provide accurate early warnings. In recent years, machine learning tools have been tested as an alternative to numerical weather prediction models that rely on an explicit physical description of the atmospheric processes. This paper presents an innovative approach using artificial neural networks to forecast the storm’s trajectory, its radar reflectivity (which is related to the rainfall intensity), and the area hit by the storm. The results obtained on a northern Italian region often affected by convective storms in spring and summer show that the neural model is accurate and much faster than classical weather prediction models, making real-time early warnings possible. View this paper
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Articles (13)

  • Article
  • Open Access
14 Citations
4,095 Views
23 Pages

20 June 2024

Transportation significantly influences greenhouse gas emissions—particularly carbon dioxide (CO2)—thereby affecting climate, health, and various socioeconomic aspects. Therefore, in developing and implementing targeted and effective poli...

  • Article
  • Open Access
2,496 Views
6 Pages

18 June 2024

Minimum trace reconciliation, developed by Wickramasuriya et al., 2019, is an innovation in the literature on forecast reconciliation. The proof, however, has a gap, and the idea is not easy to extend to more general situations. This paper fills the...

  • Article
  • Open Access
3 Citations
7,966 Views
22 Pages

Machine Learning-Enhanced Pairs Trading

  • Eli Hadad,
  • Sohail Hodarkar,
  • Beakal Lemeneh and
  • Dennis Shasha

11 June 2024

Forecasting returns in financial markets is notoriously challenging due to the resemblance of price changes to white noise. In this paper, we propose novel methods to address this challenge. Employing high-frequency Brazilian stock market data at one...

  • Article
  • Open Access
2 Citations
4,258 Views
16 Pages

4 June 2024

In this article, we document the use of hail cannons in Mexico to dispel or suppress heavy rain episodes, a common practice among farmers, without scientific evidence to support its effectiveness. This study uses two rain databases: one compiled from...

  • Article
  • Open Access
1 Citations
3,160 Views
14 Pages

26 May 2024

Deep learning has recently demonstrated the ability to predict long-term patient risk and its stratification when trained on imaging data such as chest radiographs. However, existing methods formulate estimating patient risk as a binary classificatio...

  • Article
  • Open Access
2,609 Views
26 Pages

22 May 2024

The modeling and simulation of societies requires identifying the spatio-temporal patterns of people’s activities. In urban areas, it is key to effective urban planning; it can be used in real estate projects to predict their future impacts on...

  • Article
  • Open Access
6 Citations
2,436 Views
21 Pages

Utilizing the Honeybees Mating-Inspired Firefly Algorithm to Extract Parameters of the Wind Speed Weibull Model

  • Abubaker Younis,
  • Fatima Belabbes,
  • Petru Adrian Cotfas and
  • Daniel Tudor Cotfas

22 May 2024

This study introduces a novel adjustment to the firefly algorithm (FA) through the integration of rare instances of cannibalism among fireflies, culminating in the development of the honeybee mating-based firefly algorithm (HBMFA). The IEEE Congress...

  • Article
  • Open Access
2 Citations
3,256 Views
14 Pages

21 May 2024

Evaluation of water quality and accurate prediction of water pollution indicators are key components in water resource management and water pollution control. The use of biological early warning systems (BEWS), in which living organisms are used as b...

  • Article
  • Open Access
4 Citations
4,355 Views
17 Pages

Forecasting Convective Storms Trajectory and Intensity by Neural Networks

  • Niccolò Borghi,
  • Giorgio Guariso and
  • Matteo Sangiorgio

19 May 2024

Convective storms represent a dangerous atmospheric phenomenon, particularly for the heavy and concentrated precipitation they can trigger. Given their high velocity and variability, their prediction is challenging, though it is crucial to issue reli...

  • Article
  • Open Access
2 Citations
6,685 Views
30 Pages

30 April 2024

The objective of this work is to predict the impact of technology on employment demand by profession in Spain between 2023 and 2035. The evaluation of this effect involved the comparison of two scenarios: a trend scenario obtained by predicting the e...

  • Article
  • Open Access
6 Citations
12,739 Views
17 Pages

23 April 2024

Since cryptocurrencies are among the most extensively traded financial instruments globally, predicting their price has become a crucial topic for investors. Our dataset, which includes fluctuations in Bitcoin’s hourly prices from 15 May 2018 t...

  • Article
  • Open Access
2 Citations
2,638 Views
13 Pages

Riding into Danger: Predictive Modeling for ATV-Related Injuries and Seasonal Patterns

  • Fernando Ferreira Lima dos Santos,
  • Farzaneh Khorsandi and
  • Guilherme De Moura Araujo

2 April 2024

All-Terrain Vehicles (ATVs) are popular off-road vehicles in the United States, with a staggering 10.5 million households reported to own at least one ATV. Despite their popularity, ATVs pose a significant risk of severe injuries, leading to substant...

  • Article
  • Open Access
16 Citations
5,311 Views
27 Pages

Predictive Maintenance Framework for Fault Detection in Remote Terminal Units

  • Alexios Lekidis,
  • Angelos Georgakis,
  • Christos Dalamagkas and
  • Elpiniki I. Papageorgiou

25 March 2024

The scheduled maintenance of industrial equipment is usually performed with a low frequency, as it usually leads to unpredicted downtime in business operations. Nevertheless, this confers a risk of failure in individual modules of the equipment, whic...

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Forecasting - ISSN 2571-9394