An algorithm to compute the strength of competing interactions in the Bering Sea based on pythagorean fuzzy hypergraphs

Abstract The networks of various problems have competing constituents, and there is a concern to compute the strength of competition among these entities. Competition hypergraphs capture all groups of predators that are competing in a community through their hyperedges. This paper reintroduces compe...

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Published in:Neural Computing and Applications
Main Authors: Nawaz, Hafiza Saba, Akram, Muhammad, Alcantud, José Carlos R.
Other Authors: Universidad de Salamanca
Format: Article in Journal/Newspaper
Language:English
Published: Springer Science and Business Media LLC 2021
Subjects:
Online Access:http://dx.doi.org/10.1007/s00521-021-06414-8
https://link.springer.com/content/pdf/10.1007/s00521-021-06414-8.pdf
https://link.springer.com/article/10.1007/s00521-021-06414-8/fulltext.html
id crspringernat:10.1007/s00521-021-06414-8
record_format openpolar
spelling crspringernat:10.1007/s00521-021-06414-8 2023-05-15T15:43:34+02:00 An algorithm to compute the strength of competing interactions in the Bering Sea based on pythagorean fuzzy hypergraphs Nawaz, Hafiza Saba Akram, Muhammad Alcantud, José Carlos R. Universidad de Salamanca 2021 http://dx.doi.org/10.1007/s00521-021-06414-8 https://link.springer.com/content/pdf/10.1007/s00521-021-06414-8.pdf https://link.springer.com/article/10.1007/s00521-021-06414-8/fulltext.html en eng Springer Science and Business Media LLC https://creativecommons.org/licenses/by/4.0 https://creativecommons.org/licenses/by/4.0 CC-BY Neural Computing and Applications ISSN 0941-0643 1433-3058 Artificial Intelligence Software journal-article 2021 crspringernat https://doi.org/10.1007/s00521-021-06414-8 2022-01-04T09:29:28Z Abstract The networks of various problems have competing constituents, and there is a concern to compute the strength of competition among these entities. Competition hypergraphs capture all groups of predators that are competing in a community through their hyperedges. This paper reintroduces competition hypergraphs in the context of Pythagorean fuzzy set theory, thereby producing Pythagorean fuzzy competition hypergraphs. The data of real-world ecological systems posses uncertainty, and the proposed hypergraphs can efficiently deal with such information to model wide range of competing interactions. We suggest several extensions of Pythagorean fuzzy competition hypergraphs, including Pythagorean fuzzy economic competition hypergraphs, Pythagorean fuzzy row as well as column hypergraphs, Pythagorean fuzzy k -competition hypergraphs, m -step Pythagorean fuzzy competition hypergraphs and Pythagorean fuzzy neighborhood hypergraphs. The proposed graphical structures are good tools to measure the strength of direct and indirect competing and non-competing interactions. Their aptness is illustrated through examples, and results support their intrinsic interest. We propose algorithms that help to compose some of the presented graphical structures. We consider predator-prey interactions among organisms of the Bering Sea as an application: Pythagorean fuzzy competition hypergraphs encapsulate the competing relationships among its inhabitants. Specifically, the algorithm which constructs the Pythagorean fuzzy competition hypergraphs can also compute the strength of competing and non-competing relations of this scenario. Article in Journal/Newspaper Bering Sea Springer Nature (via Crossref) Bering Sea Neural Computing and Applications
institution Open Polar
collection Springer Nature (via Crossref)
op_collection_id crspringernat
language English
topic Artificial Intelligence
Software
spellingShingle Artificial Intelligence
Software
Nawaz, Hafiza Saba
Akram, Muhammad
Alcantud, José Carlos R.
An algorithm to compute the strength of competing interactions in the Bering Sea based on pythagorean fuzzy hypergraphs
topic_facet Artificial Intelligence
Software
description Abstract The networks of various problems have competing constituents, and there is a concern to compute the strength of competition among these entities. Competition hypergraphs capture all groups of predators that are competing in a community through their hyperedges. This paper reintroduces competition hypergraphs in the context of Pythagorean fuzzy set theory, thereby producing Pythagorean fuzzy competition hypergraphs. The data of real-world ecological systems posses uncertainty, and the proposed hypergraphs can efficiently deal with such information to model wide range of competing interactions. We suggest several extensions of Pythagorean fuzzy competition hypergraphs, including Pythagorean fuzzy economic competition hypergraphs, Pythagorean fuzzy row as well as column hypergraphs, Pythagorean fuzzy k -competition hypergraphs, m -step Pythagorean fuzzy competition hypergraphs and Pythagorean fuzzy neighborhood hypergraphs. The proposed graphical structures are good tools to measure the strength of direct and indirect competing and non-competing interactions. Their aptness is illustrated through examples, and results support their intrinsic interest. We propose algorithms that help to compose some of the presented graphical structures. We consider predator-prey interactions among organisms of the Bering Sea as an application: Pythagorean fuzzy competition hypergraphs encapsulate the competing relationships among its inhabitants. Specifically, the algorithm which constructs the Pythagorean fuzzy competition hypergraphs can also compute the strength of competing and non-competing relations of this scenario.
author2 Universidad de Salamanca
format Article in Journal/Newspaper
author Nawaz, Hafiza Saba
Akram, Muhammad
Alcantud, José Carlos R.
author_facet Nawaz, Hafiza Saba
Akram, Muhammad
Alcantud, José Carlos R.
author_sort Nawaz, Hafiza Saba
title An algorithm to compute the strength of competing interactions in the Bering Sea based on pythagorean fuzzy hypergraphs
title_short An algorithm to compute the strength of competing interactions in the Bering Sea based on pythagorean fuzzy hypergraphs
title_full An algorithm to compute the strength of competing interactions in the Bering Sea based on pythagorean fuzzy hypergraphs
title_fullStr An algorithm to compute the strength of competing interactions in the Bering Sea based on pythagorean fuzzy hypergraphs
title_full_unstemmed An algorithm to compute the strength of competing interactions in the Bering Sea based on pythagorean fuzzy hypergraphs
title_sort algorithm to compute the strength of competing interactions in the bering sea based on pythagorean fuzzy hypergraphs
publisher Springer Science and Business Media LLC
publishDate 2021
url http://dx.doi.org/10.1007/s00521-021-06414-8
https://link.springer.com/content/pdf/10.1007/s00521-021-06414-8.pdf
https://link.springer.com/article/10.1007/s00521-021-06414-8/fulltext.html
geographic Bering Sea
geographic_facet Bering Sea
genre Bering Sea
genre_facet Bering Sea
op_source Neural Computing and Applications
ISSN 0941-0643 1433-3058
op_rights https://creativecommons.org/licenses/by/4.0
https://creativecommons.org/licenses/by/4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.1007/s00521-021-06414-8
container_title Neural Computing and Applications
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