Predictions of Aeroengines’ Infrared Radiation Characteristics Based on HKELM Optimized by the Improved Dung Beetle Optimizer

Predictions of Aeroengines’ Infrared Radiation Characteristics Based on HKELM Optimized by the Improved Dung Beetle Optimizer

To solve the problems of high computational cost and the long time required by the simulation and calculation of aeroengines’ exhaust systems, a method of predicting the characteristics of infrared radiation based on the hybrid kernel extreme learning machine (HKELM) optimized by the improved dung b...

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Bibliographic Details
Main Authors: Lei Qiao, Lihai Chen, Yiwen Li, Weizhuo Hua, Ping Wang, You Cui
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Sensors
Subjects:
aeroengine
infrared radiation characteristics
hybrid kernel extreme learning machine
dung beetle optimizer
Levy flight strategy
variable spiral strategy
Online Access:https://www.mdpi.com/1424-8220/24/6/1734

Internet

https://www.mdpi.com/1424-8220/24/6/1734

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