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...
Published in: | Neural Computing and Applications |
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Springer Science and Business Media LLC
2021
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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 |
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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 |
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Springer Nature (via Crossref) |
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English |
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Artificial Intelligence Software |
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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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1766377750512271360 |