Chaotic Harris Hawks Optimization with Quasi-Reflection-Based Learning: An Application to Enhance CNN Design

Chaotic Harris Hawks Optimization with Quasi-Reflection-Based Learning: An Application to Enhance CNN Design

The research presented in this manuscript proposes a novel Harris Hawks optimization algorithm with practical application for evolving convolutional neural network architecture to classify various grades of brain tumor using magnetic resonance imaging. The proposed improved Harris Hawks optimization...

Full description

Bibliographic Details
Main Authors: Jameer Basha, Nebojsa Bacanin, Nikola Vukobrat, Miodrag Zivkovic, K. Venkatachalam, Stepan Hubálovský, Pavel Trojovský
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Sensors
Subjects:
swarm intelligence
Harris Hawks optimization
exploitation–exploration trade-off
chaotic
quasi-reflection-based learning
convolutional neural networks
Online Access:https://www.mdpi.com/1424-8220/21/19/6654

Internet

https://www.mdpi.com/1424-8220/21/19/6654

Similar Items