PI-D CONTROLLER BASED ON AN IMPROVED CROW SEARCH ALGORITHM FOR CANCER GROWTH TREATMENT

The number of cancer diagnoses and deaths worldwide is rising every year despite technological advancements in diagnosing and treating multiple forms of cancer. An oncolytic virus is a type of tumour-killing virus that can infect and analyze cancer cells while mostly preserving normal cells. The onc...

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Autores principales:	Mohammed A. Hussein, Ekhlas H. Karam
Formato:	article
Lenguaje:	AR EN
Publicado:	Mustansiriyah University/College of Engineering 2021
Materias:	oncolytic virotherapy feedback mechanism biotherapy pi-d control robust control icsa pso algorithm. Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/c3a51c3a16db4d6c81f4fd2c12fe2884
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spelling	oai:doaj.org-article:c3a51c3a16db4d6c81f4fd2c12fe28842021-11-10T10:45:17ZPI-D CONTROLLER BASED ON AN IMPROVED CROW SEARCH ALGORITHM FOR CANCER GROWTH TREATMENT10.31272/jeasd.25.6.92520-09172520-0925https://doaj.org/article/c3a51c3a16db4d6c81f4fd2c12fe28842021-11-01T00:00:00Zhttps://www.iasj.net/iasj/download/fc56ce5ffd631a27https://doaj.org/toc/2520-0917https://doaj.org/toc/2520-0925The number of cancer diagnoses and deaths worldwide is rising every year despite technological advancements in diagnosing and treating multiple forms of cancer. An oncolytic virus is a type of tumour-killing virus that can infect and analyze cancer cells while mostly preserving normal cells. The oncolytic Vesicular-Stomatitis Virus therapeutic's cell cycle-specific action mathematically investigated. An optimal Proportion Integral-Derivative (PI-D) controller is introduced in this paper based on a suggested Improved Crow Search Algorithm (ICSA) to enhance the outcome of oncolytic virotherapy. The control technique was tested in a computer using MATLAB simulation. The suggested ICSA is used to tune the parameters of the PI-D controller. The ICSA used the inertia factor and boundary handle mechanism in the position update equation to balance exploration and exploitation. The simulation results show that decrease in total dose, tumour cells to 30%, the tumour remain in the treatment area from day 30 onwards. Furthermore, the ICSA algorithm outperforms the CSA and PSO algorithms by 34.5497×10-6 and 15.2573 ×10-6, respectively, indicating the robustness of treatment methods that can accomplish tumour reduction through biological parameters ambiguity.Mohammed A. HusseinEkhlas H. KaramMustansiriyah University/College of Engineeringarticleoncolytic virotherapyfeedback mechanismbiotherapypi-d controlrobust controlicsapso algorithm.Engineering (General). Civil engineering (General)TA1-2040ARENJournal of Engineering and Sustainable Development, Vol 25, Iss 6, Pp 82-90 (2021)
institution	DOAJ
collection	DOAJ
language	AR EN
topic	oncolytic virotherapy feedback mechanism biotherapy pi-d control robust control icsa pso algorithm. Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	oncolytic virotherapy feedback mechanism biotherapy pi-d control robust control icsa pso algorithm. Engineering (General). Civil engineering (General) TA1-2040 Mohammed A. Hussein Ekhlas H. Karam PI-D CONTROLLER BASED ON AN IMPROVED CROW SEARCH ALGORITHM FOR CANCER GROWTH TREATMENT
description	The number of cancer diagnoses and deaths worldwide is rising every year despite technological advancements in diagnosing and treating multiple forms of cancer. An oncolytic virus is a type of tumour-killing virus that can infect and analyze cancer cells while mostly preserving normal cells. The oncolytic Vesicular-Stomatitis Virus therapeutic's cell cycle-specific action mathematically investigated. An optimal Proportion Integral-Derivative (PI-D) controller is introduced in this paper based on a suggested Improved Crow Search Algorithm (ICSA) to enhance the outcome of oncolytic virotherapy. The control technique was tested in a computer using MATLAB simulation. The suggested ICSA is used to tune the parameters of the PI-D controller. The ICSA used the inertia factor and boundary handle mechanism in the position update equation to balance exploration and exploitation. The simulation results show that decrease in total dose, tumour cells to 30%, the tumour remain in the treatment area from day 30 onwards. Furthermore, the ICSA algorithm outperforms the CSA and PSO algorithms by 34.5497×10-6 and 15.2573 ×10-6, respectively, indicating the robustness of treatment methods that can accomplish tumour reduction through biological parameters ambiguity.
format	article
author	Mohammed A. Hussein Ekhlas H. Karam
author_facet	Mohammed A. Hussein Ekhlas H. Karam
author_sort	Mohammed A. Hussein
title	PI-D CONTROLLER BASED ON AN IMPROVED CROW SEARCH ALGORITHM FOR CANCER GROWTH TREATMENT
title_short	PI-D CONTROLLER BASED ON AN IMPROVED CROW SEARCH ALGORITHM FOR CANCER GROWTH TREATMENT
title_full	PI-D CONTROLLER BASED ON AN IMPROVED CROW SEARCH ALGORITHM FOR CANCER GROWTH TREATMENT
title_fullStr	PI-D CONTROLLER BASED ON AN IMPROVED CROW SEARCH ALGORITHM FOR CANCER GROWTH TREATMENT
title_full_unstemmed	PI-D CONTROLLER BASED ON AN IMPROVED CROW SEARCH ALGORITHM FOR CANCER GROWTH TREATMENT
title_sort	pi-d controller based on an improved crow search algorithm for cancer growth treatment
publisher	Mustansiriyah University/College of Engineering
publishDate	2021
url	https://doaj.org/article/c3a51c3a16db4d6c81f4fd2c12fe2884
work_keys_str_mv	AT mohammedahussein pidcontrollerbasedonanimprovedcrowsearchalgorithmforcancergrowthtreatment AT ekhlashkaram pidcontrollerbasedonanimprovedcrowsearchalgorithmforcancergrowthtreatment
_version_	1718440033503936512

PI-D CONTROLLER BASED ON AN IMPROVED CROW SEARCH ALGORITHM FOR CANCER GROWTH TREATMENT

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