Welcome to the InfoSci Platform
Classification of Autistic Spectrum Disorder Using Deep Neural Network With Particle Swarm Optimization

Classification of Autistic Spectrum Disorder Using Deep Neural Network With Particle Swarm Optimization

Sanat Kumar Sahu, Pratibha Verma
Copyright: © 2022 |Volume: 12 |Issue: 1 |Pages: 11
ISSN: 2155-6997|EISSN: 2155-6989|EISBN13: 9781683182122|DOI: 10.4018/IJCVIP.290398
Cite Article Cite Article

MLA

Sahu, Sanat Kumar, and Pratibha Verma. "Classification of Autistic Spectrum Disorder Using Deep Neural Network With Particle Swarm Optimization." IJCVIP vol.12, no.1 2022: pp.1-11. http://doi.org/10.4018/IJCVIP.290398

APA

Sahu, S. K. & Verma, P. (2022). Classification of Autistic Spectrum Disorder Using Deep Neural Network With Particle Swarm Optimization. International Journal of Computer Vision and Image Processing (IJCVIP), 12(1), 1-11. http://doi.org/10.4018/IJCVIP.290398

Chicago

Sahu, Sanat Kumar, and Pratibha Verma. "Classification of Autistic Spectrum Disorder Using Deep Neural Network With Particle Swarm Optimization," International Journal of Computer Vision and Image Processing (IJCVIP) 12, no.1: 1-11. http://doi.org/10.4018/IJCVIP.290398

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

In this paper, Feature Selection Technique (FST) namely Particle Swarm Optimization (PSO) has been used. The filter based PSO is a search method with Correlation-based Feature Selection (CBFS) as a fitness function. The FST has two key goals of improving classification efficiency and reducing feature counts. Artificial Neural Network (ANN) Based Multilayer Perceptron Network (MLP) and Deep Learning (DL) have been considered the classification methods on 2 benchmark Autistic Spectrum Disorder (ASD) dataset. The experimental result was compared to the non-reduced features and reduced feature of ASD datasets. The reduced feature give up enhanced results in both classifiers MLP and DL. In addition, an experimental study on the exhibitions of these methodologies has been conducted. Finally, a new trend of PSO-MLP and PSO-DL based classification model is proposed.