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An Efficient Multisensor Hybrid Data Fusion Approach Based on Artificial Neural Networks and Particle Swarm Optimization Algorithms.

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Title: An Efficient Multisensor Hybrid Data Fusion Approach Based on Artificial Neural Networks and Particle Swarm Optimization Algorithms.
Authors: Ihonock, Luc Eyembe1, eyembeluc@yahoo.fr, Essiben, Jean-François Dikoundou1,2,3, Diboma, Benjamin Salomon1,2,4, Yong, Joe Suk5, Bagwari, Ashish, ashishbagwari@gmail.com
Source: International Journal of Distributed Sensor Networks; 6/6/2024, Vol. 2024, p1-18, 18p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 179684542
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: An Efficient Multisensor Hybrid Data Fusion Approach Based on Artificial Neural Networks and Particle Swarm Optimization Algorithms.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Distributed+Sensor+Networks%22">International Journal of Distributed Sensor Networks</searchLink>; 6/6/2024, Vol. 2024, p1-18, 18p
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        Value: 10.1155/2024/8644510
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      – Code: eng
        Text: English
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        PageCount: 18
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      – TitleFull: An Efficient Multisensor Hybrid Data Fusion Approach Based on Artificial Neural Networks and Particle Swarm Optimization Algorithms.
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            NameFull: Ihonock, Luc Eyembe
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            NameFull: Essiben, Jean-François Dikoundou
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              Text: 6/6/2024
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              Y: 2024
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              Value: 2024
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