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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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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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Oscar Leonardo García-Navarrete, Adriana Correa-Guimaraes and Luis Manuel Navas-Gracia
Weeds are unwanted and invasive plants that proliferate and compete for resources such as space, water, nutrients, and sunlight, affecting the quality and productivity of the desired crops. Weed detection is crucial for the application of precision agric...
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Rohan S. Sharma and Serhat Hosder
The intent of this work was to investigate the feasibility of developing machine learning models for calculating values of airplane configuration design variables when provided time-series, mission-informed performance data. Shallow artificial neural net...
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Herve M. Kabamba, Matthew Khouzam and Michel R. Dagenais
Tracing serves as a key method for evaluating the performance of microservices-based architectures, which are renowned for their scalability, resource efficiency, and high availability. Despite their advantages, these architectures often pose unique debu...
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Peng Zhang, Qin Qin, Shijie Zhang, Xiangtian Zhao, Xiaoliang Yan, Wei Wang and Hongbin Zhang
Remote sensing has become an essential tool for geological exploration, disaster monitoring, emergency rescue, and environmental supervision, while the limited number of remote sensing satellites and ground stations restricts the timeliness of remote sen...
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Ben Campbell and Lawrence Dale Thomas
This article describes a new alternative approach to satellite constellation deployment by incorporating momentum exchange tethers (METs). Traditional methods of deploying satellite constellations have limitations, typically involving costly propulsion s...
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Benjamin Burrichter, Juliana Koltermann da Silva, Andre Niemann and Markus Quirmbach
This study employs a temporal fusion transformer (TFT) for predicting overflow from sewer manholes during heavy rainfall events. The TFT utilised is capable of forecasting overflow hydrographs at the manhole level and was tested on a sewer network with 9...
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Jing Liu, Xuesong Hai and Keqin Li
Massive amounts of data drive the performance of deep learning models, but in practice, data resources are often highly dispersed and bound by data privacy and security concerns, making it difficult for multiple data sources to share their local data dir...
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Alper Taner, Mahtem Teweldemedhin Mengstu, Kemal Çagatay Selvi, Hüseyin Duran, Ibrahim Gür and Nicoleta Ungureanu
Having the advantages of speed, suitability and high accuracy, computer vision has been effectively utilized as a non-destructive approach to automatically recognize and classify fruits and vegetables, to meet the increased demand for food quality-sensin...
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