Scaled Conjugate Gradient Neural Intelligence for Motion Parameters Prediction of Markov Chain Underwater Maneuvering Target

Scaled Conjugate Gradient Neural Intelligence for Motion Parameters Prediction of Markov Chain Underwater Maneuvering Target

This study proposes a novel application of neural computing based on deep learning for the real-time prediction of motion parameters for underwater maneuvering object. The intelligent strategy utilizes the capabilities of Scaled Conjugate Gradient Neural Intelligence (SCGNI) to estimate the dynamics...

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Bibliographic Details
Main Authors: Wasiq Ali, Habib Hussain Zuberi, Xin Qing, Abdulaziz Miyajan, Amar Jaffar, Ayman Alharbi
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Journal of Marine Science and Engineering
Subjects:
deep learning
motion parameters
state-space
underwater acoustics
passive bearings
Monte Carlo
Online Access:https://www.mdpi.com/2077-1312/12/2/240

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