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Titlebook: Enhanced Living Environments; Algorithms, Architec Ivan Ganchev,Nuno M. Garcia,Rossitza Goleva Book‘‘‘‘‘‘‘‘ 2019 The Editor(s) (if applicab

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21#
發(fā)表于 2025-3-25 03:52:14 | 只看該作者
Book‘‘‘‘‘‘‘‘ 2019onments (AAPELE)”. The concept of Enhanced Living Environments (ELE) refers to the area of Ambient Assisted Living (AAL) that is more related with Information and Communication Technologies (ICT). Effective ELE solutions require appropriate ICT algorithms, architectures, platforms, and systems, havi
22#
發(fā)表于 2025-3-25 10:26:44 | 只看該作者
https://doi.org/10.1007/978-3-030-59533-3ROAFTN classifier. The improved PROAFTN classifier is described and compared to well known classifiers, in terms of their learning methodology and classification accuracy. Through this chapter we have shown the ability of the metaheuristics when embedded to PROAFTN method to solve efficiency the classification problems.
23#
發(fā)表于 2025-3-25 12:51:28 | 只看該作者
Combining Machine Learning and Metaheuristics Algorithms for Classification Method PROAFTN,ROAFTN classifier. The improved PROAFTN classifier is described and compared to well known classifiers, in terms of their learning methodology and classification accuracy. Through this chapter we have shown the ability of the metaheuristics when embedded to PROAFTN method to solve efficiency the classification problems.
24#
發(fā)表于 2025-3-25 16:12:39 | 只看該作者
25#
發(fā)表于 2025-3-25 23:43:13 | 只看該作者
26#
發(fā)表于 2025-3-26 02:19:19 | 只看該作者
27#
發(fā)表于 2025-3-26 06:56:39 | 只看該作者
Development and Evaluation of Methodology for Personal Recommendations Applicable in Connected Heallidated using real dataset collected in a certain period of time from a community of 1000 active users. Recommendations generated by the system were related to weight loss. The results show that our generated recommendations have high accuracy, up to 95%.
28#
發(fā)表于 2025-3-26 11:10:13 | 只看該作者
29#
發(fā)表于 2025-3-26 15:52:57 | 只看該作者
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發(fā)表于 2025-3-26 17:35:30 | 只看該作者
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