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Luis Adán Félix-Salazar, Emigdio Marín-Enríquez, Eugenio Alberto Aragón-Noriega and Jorge Saul Ramirez-Perez
During the last 50 years, the increase in the efforts of the longline fleet in the Eastern Pacific Ocean (EPO) resulted in an increase in the capture of the swordfish Xiphias gladius. We analyzed a historical database of swordfish catches (1980?2020) rep...
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Tianao Qin, Ruixin Chen, Rufu Qin and Yang Yu
Time series prediction is an effective tool for marine scientific research. The Hierarchical Temporal Memory (HTM) model has advantages over traditional recurrent neural network (RNN)-based models due to its online learning and prediction capabilities. G...
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MohammadHossein Reshadi, Wen Li, Wenjie Xu, Precious Omashor, Albert Dinh, Scott Dick, Yuntong She and Michael Lipsett
Anomaly detection in data streams (and particularly time series) is today a vitally important task. Machine learning algorithms are a common design for achieving this goal. In particular, deep learning has, in the last decade, proven to be substantially ...
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Shurong Peng, Lijuan Guo, Haoyu Huang, Xiaoxu Liu and Jiayi Peng
The integration of large-scale wind power into the power grid threatens the stable operation of the power system. Traditional wind power prediction is based on time series without considering the variability between wind turbines in different locations. ...
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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...
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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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Mattia Neroni, Massimo Bertolini and Angel A. Juan
In automated storage and retrieval systems (AS/RSs), the utilization of intelligent algorithms can reduce the makespan required to complete a series of input/output operations. This paper introduces a simulation optimization algorithm designed to minimiz...
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Yuzhu Zhang and Hao Xu
This study investigates the problem of decentralized dynamic resource allocation optimization for ad-hoc network communication with the support of reconfigurable intelligent surfaces (RIS), leveraging a reinforcement learning framework. In the present co...
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Sergio Bonaccorsi, Marco Felice Montaruli, Pierluigi Di Lizia, Moreno Peroni, Alessandro Panico, Marco Rigamonti and Francesco Del Prete
The increasing number of objects in Earth orbit has encouraged the development of space surveillance and tracking (SST) applications. A critical aspect of SST is the identification and characterization of close encounters between pairs of space objects. ...
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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...
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