q-Rung Orthopair Fuzzy Rough Einstein Aggregation Information-Based EDAS Method: Applications in Robotic Agrifarming

The main purpose of this manuscript is to present a novel idea on the q-rung orthopair fuzzy rough set (q-ROFRS) by the hybridized notion of q-ROFRSs and rough sets (RSs) and discuss its basic operations. Furthermore, by utilizing the developed concept, a list of q-ROFR Einstein weighted averaging a...

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Autores principales:	Shahzaib Ashraf, Noor Rehman, Azmat Hussain, Hussain AlSalman, Abdu H. Gumaei
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/d06afa7d5aa84b5e8f05d5dc4ea3c378
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spelling	oai:doaj.org-article:d06afa7d5aa84b5e8f05d5dc4ea3c3782021-11-08T02:35:43Zq-Rung Orthopair Fuzzy Rough Einstein Aggregation Information-Based EDAS Method: Applications in Robotic Agrifarming1687-527310.1155/2021/5520264https://doaj.org/article/d06afa7d5aa84b5e8f05d5dc4ea3c3782021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/5520264https://doaj.org/toc/1687-5273The main purpose of this manuscript is to present a novel idea on the q-rung orthopair fuzzy rough set (q-ROFRS) by the hybridized notion of q-ROFRSs and rough sets (RSs) and discuss its basic operations. Furthermore, by utilizing the developed concept, a list of q-ROFR Einstein weighted averaging and geometric aggregation operators are presented which are based on algebraic and Einstein norms. Similarly, some interesting characteristics of these operators are initiated. Moreover, the concept of the entropy and distance measures is presented to utilize the decision makers’ unknown weights as well as attributes’ weight information. The EDAS (evaluation based on distance from average solution) methodology plays a crucial role in decision-making challenges, especially when the problems of multicriteria group decision-making (MCGDM) include more competing criteria. The core of this study is to develop a decision-making algorithm based on the entropy measure, aggregation information, and EDAS methodology to handle the uncertainty in real-word decision-making problems (DMPs) under q-rung orthopair fuzzy rough information. To show the superiority and applicability of the developed technique, a numerical case study of a real-life DMP in agriculture farming is considered. Findings indicate that the suggested decision-making model is much more efficient and reliable to tackle uncertain information based on q-ROFR information.Shahzaib AshrafNoor RehmanAzmat HussainHussain AlSalmanAbdu H. GumaeiHindawi LimitedarticleComputer applications to medicine. Medical informaticsR858-859.7Neurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENComputational Intelligence and Neuroscience, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Shahzaib Ashraf Noor Rehman Azmat Hussain Hussain AlSalman Abdu H. Gumaei q-Rung Orthopair Fuzzy Rough Einstein Aggregation Information-Based EDAS Method: Applications in Robotic Agrifarming
description	The main purpose of this manuscript is to present a novel idea on the q-rung orthopair fuzzy rough set (q-ROFRS) by the hybridized notion of q-ROFRSs and rough sets (RSs) and discuss its basic operations. Furthermore, by utilizing the developed concept, a list of q-ROFR Einstein weighted averaging and geometric aggregation operators are presented which are based on algebraic and Einstein norms. Similarly, some interesting characteristics of these operators are initiated. Moreover, the concept of the entropy and distance measures is presented to utilize the decision makers’ unknown weights as well as attributes’ weight information. The EDAS (evaluation based on distance from average solution) methodology plays a crucial role in decision-making challenges, especially when the problems of multicriteria group decision-making (MCGDM) include more competing criteria. The core of this study is to develop a decision-making algorithm based on the entropy measure, aggregation information, and EDAS methodology to handle the uncertainty in real-word decision-making problems (DMPs) under q-rung orthopair fuzzy rough information. To show the superiority and applicability of the developed technique, a numerical case study of a real-life DMP in agriculture farming is considered. Findings indicate that the suggested decision-making model is much more efficient and reliable to tackle uncertain information based on q-ROFR information.
format	article
author	Shahzaib Ashraf Noor Rehman Azmat Hussain Hussain AlSalman Abdu H. Gumaei
author_facet	Shahzaib Ashraf Noor Rehman Azmat Hussain Hussain AlSalman Abdu H. Gumaei
author_sort	Shahzaib Ashraf
title	q-Rung Orthopair Fuzzy Rough Einstein Aggregation Information-Based EDAS Method: Applications in Robotic Agrifarming
title_short	q-Rung Orthopair Fuzzy Rough Einstein Aggregation Information-Based EDAS Method: Applications in Robotic Agrifarming
title_full	q-Rung Orthopair Fuzzy Rough Einstein Aggregation Information-Based EDAS Method: Applications in Robotic Agrifarming
title_fullStr	q-Rung Orthopair Fuzzy Rough Einstein Aggregation Information-Based EDAS Method: Applications in Robotic Agrifarming
title_full_unstemmed	q-Rung Orthopair Fuzzy Rough Einstein Aggregation Information-Based EDAS Method: Applications in Robotic Agrifarming
title_sort	q-rung orthopair fuzzy rough einstein aggregation information-based edas method: applications in robotic agrifarming
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/d06afa7d5aa84b5e8f05d5dc4ea3c378
work_keys_str_mv	AT shahzaibashraf qrungorthopairfuzzyrougheinsteinaggregationinformationbasededasmethodapplicationsinroboticagrifarming AT noorrehman qrungorthopairfuzzyrougheinsteinaggregationinformationbasededasmethodapplicationsinroboticagrifarming AT azmathussain qrungorthopairfuzzyrougheinsteinaggregationinformationbasededasmethodapplicationsinroboticagrifarming AT hussainalsalman qrungorthopairfuzzyrougheinsteinaggregationinformationbasededasmethodapplicationsinroboticagrifarming AT abduhgumaei qrungorthopairfuzzyrougheinsteinaggregationinformationbasededasmethodapplicationsinroboticagrifarming
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q-Rung Orthopair Fuzzy Rough Einstein Aggregation Information-Based EDAS Method: Applications in Robotic Agrifarming

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