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Diego Sánchez-Moreno, Vivian F. López Batista, María Dolores Muñoz Vicente, Ángel Luis Sánchez Lázaro and María N. Moreno-García
Information from social networks is currently being widely used in many application domains, although in the music recommendation area, its use is less common because of the limited availability of social data. However, most streaming platforms allow for...
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Changhao Wu, Siyang He, Zengshan Yin and Chongbin Guo
Large-scale low Earth orbit (LEO) remote satellite constellations have become a brand new, massive source of space data. Federated learning (FL) is considered a promising distributed machine learning technology that can communicate optimally using these ...
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Angel E. Muñoz-Zavala, Jorge E. Macías-Díaz, Daniel Alba-Cuéllar and José A. Guerrero-Díaz-de-León
This paper reviews the application of artificial neural network (ANN) models to time series prediction tasks. We begin by briefly introducing some basic concepts and terms related to time series analysis, and by outlining some of the most popular ANN arc...
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Mojtaba Nayyeri, Modjtaba Rouhani, Hadi Sadoghi Yazdi, Marko M. Mäkelä, Alaleh Maskooki and Yury Nikulin
One of the main disadvantages of the traditional mean square error (MSE)-based constructive networks is their poor performance in the presence of non-Gaussian noises. In this paper, we propose a new incremental constructive network based on the correntro...
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Ana Corceiro, Nuno Pereira, Khadijeh Alibabaei and Pedro D. Gaspar
The global population?s rapid growth necessitates a 70% increase in agricultural production, posing challenges exacerbated by weed infestation and herbicide drawbacks. To address this, machine learning (ML) models, particularly convolutional neural netwo...
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