Fractal and chaotic map-enhanced grey wolf optimization for robust fire detection in deep convolutional neural networks
Abstract This paper introduces a novel approach to enhancing the architecture of deep convolutional neural networks, addressing issues of self-design. The proposed strategy leverages the grey wolf optimizer and the multi-scale fractal chaotic map search scheme as fundamental components to enhance ex...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-95519-4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850265836581814272 |
|---|---|
| author | Yassine Bouteraa Mohammad Khishe |
| author_facet | Yassine Bouteraa Mohammad Khishe |
| author_sort | Yassine Bouteraa |
| collection | DOAJ |
| description | Abstract This paper introduces a novel approach to enhancing the architecture of deep convolutional neural networks, addressing issues of self-design. The proposed strategy leverages the grey wolf optimizer and the multi-scale fractal chaotic map search scheme as fundamental components to enhance exploration and exploitation, thereby improving the classification task. Several experiments validate the method, demonstrating an impressive 87.37% accuracy across 95 random trials, outperforming 23 state-of-the-art classifiers in the study’s nine datasets. This work underscores the potential of chaotic/fractal and bio-inspired paradigms in advancing neural architecture. |
| format | Article |
| id | doaj-art-06b3e39ce97c46bda4aed635210c1910 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-06b3e39ce97c46bda4aed635210c19102025-08-20T01:54:19ZengNature PortfolioScientific Reports2045-23222025-04-0115113510.1038/s41598-025-95519-4Fractal and chaotic map-enhanced grey wolf optimization for robust fire detection in deep convolutional neural networksYassine Bouteraa0Mohammad Khishe1Department of Computer Engineering, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz UniversityDepartemant of Electronic Engineering, Imam Khomeini Naval University of NowshahrAbstract This paper introduces a novel approach to enhancing the architecture of deep convolutional neural networks, addressing issues of self-design. The proposed strategy leverages the grey wolf optimizer and the multi-scale fractal chaotic map search scheme as fundamental components to enhance exploration and exploitation, thereby improving the classification task. Several experiments validate the method, demonstrating an impressive 87.37% accuracy across 95 random trials, outperforming 23 state-of-the-art classifiers in the study’s nine datasets. This work underscores the potential of chaotic/fractal and bio-inspired paradigms in advancing neural architecture.https://doi.org/10.1038/s41598-025-95519-4Chaotic mapsFractalsGray Wolf optimizerImage classificationInternet protocol |
| spellingShingle | Yassine Bouteraa Mohammad Khishe Fractal and chaotic map-enhanced grey wolf optimization for robust fire detection in deep convolutional neural networks Scientific Reports Chaotic maps Fractals Gray Wolf optimizer Image classification Internet protocol |
| title | Fractal and chaotic map-enhanced grey wolf optimization for robust fire detection in deep convolutional neural networks |
| title_full | Fractal and chaotic map-enhanced grey wolf optimization for robust fire detection in deep convolutional neural networks |
| title_fullStr | Fractal and chaotic map-enhanced grey wolf optimization for robust fire detection in deep convolutional neural networks |
| title_full_unstemmed | Fractal and chaotic map-enhanced grey wolf optimization for robust fire detection in deep convolutional neural networks |
| title_short | Fractal and chaotic map-enhanced grey wolf optimization for robust fire detection in deep convolutional neural networks |
| title_sort | fractal and chaotic map enhanced grey wolf optimization for robust fire detection in deep convolutional neural networks |
| topic | Chaotic maps Fractals Gray Wolf optimizer Image classification Internet protocol |
| url | https://doi.org/10.1038/s41598-025-95519-4 |
| work_keys_str_mv | AT yassinebouteraa fractalandchaoticmapenhancedgreywolfoptimizationforrobustfiredetectionindeepconvolutionalneuralnetworks AT mohammadkhishe fractalandchaoticmapenhancedgreywolfoptimizationforrobustfiredetectionindeepconvolutionalneuralnetworks |