Optimizing the Probabilistic Neural Network Model with the Improved Manta Ray Foraging Optimization Algorithm to Identify Pressure Fluctuation Signal Features

Optimizing the Probabilistic Neural Network Model with the Improved Manta Ray Foraging Optimization Algorithm to Identify Pressure Fluctuation Signal Features

To improve the identification accuracy of pressure fluctuation signals in the draft tube of hydraulic turbines, this study proposes an improved manta ray foraging optimization (ITMRFO) algorithm to optimize the identification method of a probabilistic neural network (PNN). Specifically, first, discr...

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Bibliographic Details
Main Authors: Xiyuan Liu, Liying Wang, Hongyan Yan, Qingjiao Cao, Luyao Zhang, Weiguo Zhao
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Biomimetics
Subjects:
hydraulic turbine
pressure fluctuation
manta ray foraging optimization algorithm
probabilistic neural network
signal identification
Online Access:https://www.mdpi.com/2313-7673/9/1/32

Internet

https://www.mdpi.com/2313-7673/9/1/32

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