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Abstract: The protection of planet Earth, its inhabitants, and all living beings requires the identification of potentially dangerous objects, ...
The viability of classifying whether objects are potentially dangerous for Earth is confirmed, and to increase the performance of the models, ...
This research proposes the use of ELMs to distinguish between potentially dangerous objects and those that are not. The ELMs applied in this study include the ...
Abstract—The protection of planet Earth, its inhabitants, and all living beings requires the identification of potentially dangerous objects, the simulation ...
Extreme learning machine (ELM) for detection of hazardous near Earth objects. The protection of planet Earth, its inhabitants, and all living beings requires ...
Aug 8, 2024 · As well as, Yao Wang [17] has applied seven machine learning algorithms to predict the hazardous near-earth objects from the NASA-Nearest Earth ...
Precision: With a precision score of approximately 81.16%, the model demonstrates its ability to identify hazardous NEOs with a relatively low rate of false ...
Missing: Extreme (ELM)
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Bibliographic details on Extreme Learning Machine (ELM) for Detection of Hazardous Near Earth Objects.
Extreme learning machine (ELM) for detection of hazardous near Earth objects ... The protection of planet Earth, its inhabitants, and all living beings requires ...
Sep 16, 2024 · The purpose of this study is to use multiple classification algorithm from machine learning to predict hazardous asteroids that orbit Earth.