Artificial Neural Network Tuning by Improved Sine Cosine Algorithm for HealthCare 4.0

Masa Gajevic; Nemanja Milutinovic; Jelena Krstovic; Luka Jovanovic; Miodrag Zivkovic; Marina Marjanovic; Catalin Stoean

doi:10.2991/978-94-6463-110-4_21

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Artificial Neural Network Tuning by Improved Sine Cosine Algorithm for HealthCare 4.0

Authors

Masa Gajevic¹, Nemanja Milutinovic¹, Jelena Krstovic¹, Luka Jovanovic¹, Miodrag Zivkovic¹^{, *}, Marina Marjanovic¹, Catalin Stoean²

¹Singidunum University, Danijelova 32, 11000, Belgrade, Serbia

²Faculty of Sciences, University of Craiova, Str. A.I. Cuza, Nr. 13, 200585, Craiova, Romania

^*Corresponding author. Email: mzivkovic@singidunum.ac.rs

Corresponding Author

Miodrag Zivkovic

Available Online 30 January 2023.

DOI: 10.2991/978-94-6463-110-4_21 How to use a DOI?
Keywords: Healthcare 4.0; Sine Cosine Algorithm; Artificial intelligence; Optimization; Metaheuristics
Abstract: This paper explores classification of datasets for Healthcare 4.0 using artificial neural networks which are tuned by improved sine cosine algorithm (SCA). Healthcare 4.0 themes include internet of things (IoT), industrial IoT (IIoT), cognitive computing, artificial intelligence, cloud computing, fog computing, edge computing, and other industry 4.0 procedures. Health issues identification are critical since prompt treatment improves the quality of life for individuals affected. One of the most difficult challenges for artificial intelligence (AI) is selecting control parameters that are appropriate for the situation at hand. This paper presents a metaheuristics-based method for training the artificial neural network, by utilizing the SCA.
Copyright: © 2023 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 1st International Conference on Innovation in Information Technology and Business (ICIITB 2022)
Series: Advances in Computer Science Research
Publication Date: 30 January 2023
ISBN: 10.2991/978-94-6463-110-4_21
ISSN: 2352-538X
DOI: 10.2991/978-94-6463-110-4_21 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Masa Gajevic
AU  - Nemanja Milutinovic
AU  - Jelena Krstovic
AU  - Luka Jovanovic
AU  - Miodrag Zivkovic
AU  - Marina Marjanovic
AU  - Catalin Stoean
PY  - 2023
DA  - 2023/01/30
TI  - Artificial Neural Network Tuning by Improved Sine Cosine Algorithm for HealthCare 4.0
BT  - Proceedings of the 1st International Conference on Innovation in Information Technology and Business (ICIITB 2022)
PB  - Atlantis Press
SP  - 289
EP  - 305
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-110-4_21
DO  - 10.2991/978-94-6463-110-4_21
ID  - Gajevic2023
ER  -

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