An Employment of the Evolutionary Algorithms in Training of Neuro Fuzzy Inference System for Forecasting Personnel Radiation Exposure

Armin Kobilica; Anas A. Abudaqa; Mustafa Ghaleb

doi:10.1109/ICIT58056.2023.10225935

An Employment of the Evolutionary Algorithms in Training of Neuro Fuzzy Inference System for Forecasting Personnel Radiation Exposure

Armin Kobilica
, Anas A. Abudaqa
, Mustafa Ghaleb

Interdisciplinary Research Center for Intelligent Secure Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Evolutionary algorithms have gained widespread recognition as a viable approach to numerous optimization problems that are characterized by infeasible optimal solutions, owing to the presence of large search spaces and computational limitations. Forecasting personnel radiation exposure can be one of these problems. Radiation exposure poses risks to various practitioners as well as patients in the healthcare facilities. In this study, we model the problem as a specific time series instance. Moreover, we investigate the impact of the training an adaptive neuro fuzzy system using evolutionary algorithms, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), on the overall performance of forecasting personnel radiation exposure. The results show that GA and PSO could provide effective solution. On the other hand, they might be highly affected by the initial state of the fuzzy inference system leading to unstable performances. We recommend further experimentation with a combination of other advanced optimization and machine learning methods to assure the most effective results.

Original language	English
Title of host publication	2023 International Conference on Information Technology
Subtitle of host publication	Cybersecurity Challenges for Sustainable Cities, ICIT 2023 - Proceeding
Editors	Khalid Mohammad Jaber
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	428-434
Number of pages	7
ISBN (Electronic)	9798350320060
DOIs	https://doi.org/10.1109/ICIT58056.2023.10225935
State	Published - 2023
Event	11th International Conference on Information Technology, ICIT 2023 - Amman, Jordan Duration: 9 Aug 2023 → 10 Aug 2023

Publication series

Name	2023 International Conference on Information Technology: Cybersecurity Challenges for Sustainable Cities, ICIT 2023 - Proceeding

Conference

Conference	11th International Conference on Information Technology, ICIT 2023
Country/Territory	Jordan
City	Amman
Period	9/08/23 → 10/08/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

evolutionary algorithms
genetic algorithm (GA)
particle swarm optimization (PSO)
radiation exposure
time series forecasting

ASJC Scopus subject areas

Urban Studies
Artificial Intelligence
Computer Networks and Communications
Information Systems
Information Systems and Management
Renewable Energy, Sustainability and the Environment

Access to Document

10.1109/ICIT58056.2023.10225935

Cite this

Kobilica, A., Abudaqa, A. A., & Ghaleb, M. (2023). An Employment of the Evolutionary Algorithms in Training of Neuro Fuzzy Inference System for Forecasting Personnel Radiation Exposure. In K. M. Jaber (Ed.), 2023 International Conference on Information Technology: Cybersecurity Challenges for Sustainable Cities, ICIT 2023 - Proceeding (pp. 428-434). (2023 International Conference on Information Technology: Cybersecurity Challenges for Sustainable Cities, ICIT 2023 - Proceeding). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIT58056.2023.10225935

Kobilica, Armin ; Abudaqa, Anas A. ; Ghaleb, Mustafa. / An Employment of the Evolutionary Algorithms in Training of Neuro Fuzzy Inference System for Forecasting Personnel Radiation Exposure. 2023 International Conference on Information Technology: Cybersecurity Challenges for Sustainable Cities, ICIT 2023 - Proceeding. editor / Khalid Mohammad Jaber. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 428-434 (2023 International Conference on Information Technology: Cybersecurity Challenges for Sustainable Cities, ICIT 2023 - Proceeding).

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title = "An Employment of the Evolutionary Algorithms in Training of Neuro Fuzzy Inference System for Forecasting Personnel Radiation Exposure",

abstract = "Evolutionary algorithms have gained widespread recognition as a viable approach to numerous optimization problems that are characterized by infeasible optimal solutions, owing to the presence of large search spaces and computational limitations. Forecasting personnel radiation exposure can be one of these problems. Radiation exposure poses risks to various practitioners as well as patients in the healthcare facilities. In this study, we model the problem as a specific time series instance. Moreover, we investigate the impact of the training an adaptive neuro fuzzy system using evolutionary algorithms, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), on the overall performance of forecasting personnel radiation exposure. The results show that GA and PSO could provide effective solution. On the other hand, they might be highly affected by the initial state of the fuzzy inference system leading to unstable performances. We recommend further experimentation with a combination of other advanced optimization and machine learning methods to assure the most effective results.",

keywords = "evolutionary algorithms, genetic algorithm (GA), particle swarm optimization (PSO), radiation exposure, time series forecasting",

author = "Armin Kobilica and Abudaqa, \{Anas A.\} and Mustafa Ghaleb",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 11th International Conference on Information Technology, ICIT 2023 ; Conference date: 09-08-2023 Through 10-08-2023",

year = "2023",

doi = "10.1109/ICIT58056.2023.10225935",

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series = "2023 International Conference on Information Technology: Cybersecurity Challenges for Sustainable Cities, ICIT 2023 - Proceeding",

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Kobilica, A, Abudaqa, AA & Ghaleb, M 2023, An Employment of the Evolutionary Algorithms in Training of Neuro Fuzzy Inference System for Forecasting Personnel Radiation Exposure. in KM Jaber (ed.), 2023 International Conference on Information Technology: Cybersecurity Challenges for Sustainable Cities, ICIT 2023 - Proceeding. 2023 International Conference on Information Technology: Cybersecurity Challenges for Sustainable Cities, ICIT 2023 - Proceeding, Institute of Electrical and Electronics Engineers Inc., pp. 428-434, 11th International Conference on Information Technology, ICIT 2023, Amman, Jordan, 9/08/23. https://doi.org/10.1109/ICIT58056.2023.10225935

An Employment of the Evolutionary Algorithms in Training of Neuro Fuzzy Inference System for Forecasting Personnel Radiation Exposure. / Kobilica, Armin; Abudaqa, Anas A.; Ghaleb, Mustafa.
2023 International Conference on Information Technology: Cybersecurity Challenges for Sustainable Cities, ICIT 2023 - Proceeding. ed. / Khalid Mohammad Jaber. Institute of Electrical and Electronics Engineers Inc., 2023. p. 428-434 (2023 International Conference on Information Technology: Cybersecurity Challenges for Sustainable Cities, ICIT 2023 - Proceeding).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2023

Y1 - 2023

N2 - Evolutionary algorithms have gained widespread recognition as a viable approach to numerous optimization problems that are characterized by infeasible optimal solutions, owing to the presence of large search spaces and computational limitations. Forecasting personnel radiation exposure can be one of these problems. Radiation exposure poses risks to various practitioners as well as patients in the healthcare facilities. In this study, we model the problem as a specific time series instance. Moreover, we investigate the impact of the training an adaptive neuro fuzzy system using evolutionary algorithms, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), on the overall performance of forecasting personnel radiation exposure. The results show that GA and PSO could provide effective solution. On the other hand, they might be highly affected by the initial state of the fuzzy inference system leading to unstable performances. We recommend further experimentation with a combination of other advanced optimization and machine learning methods to assure the most effective results.

AB - Evolutionary algorithms have gained widespread recognition as a viable approach to numerous optimization problems that are characterized by infeasible optimal solutions, owing to the presence of large search spaces and computational limitations. Forecasting personnel radiation exposure can be one of these problems. Radiation exposure poses risks to various practitioners as well as patients in the healthcare facilities. In this study, we model the problem as a specific time series instance. Moreover, we investigate the impact of the training an adaptive neuro fuzzy system using evolutionary algorithms, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), on the overall performance of forecasting personnel radiation exposure. The results show that GA and PSO could provide effective solution. On the other hand, they might be highly affected by the initial state of the fuzzy inference system leading to unstable performances. We recommend further experimentation with a combination of other advanced optimization and machine learning methods to assure the most effective results.

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ER -

Kobilica A, Abudaqa AA, Ghaleb M. An Employment of the Evolutionary Algorithms in Training of Neuro Fuzzy Inference System for Forecasting Personnel Radiation Exposure. In Jaber KM, editor, 2023 International Conference on Information Technology: Cybersecurity Challenges for Sustainable Cities, ICIT 2023 - Proceeding. Institute of Electrical and Electronics Engineers Inc. 2023. p. 428-434. (2023 International Conference on Information Technology: Cybersecurity Challenges for Sustainable Cities, ICIT 2023 - Proceeding). doi: 10.1109/ICIT58056.2023.10225935

An Employment of the Evolutionary Algorithms in Training of Neuro Fuzzy Inference System for Forecasting Personnel Radiation Exposure

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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