Application of artificial neural network method in predicting contemporary Iranian family relationships
Virtual social networks play a very important role in social change, especially changes in the structural and emotional relationships of the family. But predicting these changes is very important today. But what method can be used to predict structural changes in the family? This study intends to in...
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| Format: | Article |
| Language: | fas |
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پژوهشگاه حوزه و دانشگاه
2022-06-01
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| Series: | روش شناسی علوم انسانی |
| Subjects: | |
| Online Access: | https://method.rihu.ac.ir/article_1951_f7f1192fe8a7cbcc743cf237345e5f50.pdf |
| _version_ | 1797303844867145728 |
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| author | Majid Kafi Seyyede Marziye Shoa Hashemi Masoud monjezi Seyed Mohsen Fattahi |
| author_facet | Majid Kafi Seyyede Marziye Shoa Hashemi Masoud monjezi Seyed Mohsen Fattahi |
| author_sort | Majid Kafi |
| collection | DOAJ |
| description | Virtual social networks play a very important role in social change, especially changes in the structural and emotional relationships of the family. But predicting these changes is very important today. But what method can be used to predict structural changes in the family? This study intends to introduce one of these methods, which is a subset of artificial intelligence, called artificial neural network and as an example to show its effectiveness in predicting the relationships of families affected by virtual social networks. Therefore, the research question is formulated in such a way that by what method or methods can the consequences of the impact of virtual social networks on family relationships be predicted? Since this research is a quantitative research, data collection was done by a questionnaire and the research model was operational. The research model is a fuzzy field statistical model. The result of the research is the prediction of four types of committed, unsuccessful, incompatible and broken families, which were shown on the fuzzy spectrum as follows: Committed family: 75 to 100%; Unsuccessful family: 50 to 75%; Incompatible family 25 to 50 percent and broken family 0 to 25 percent. |
| first_indexed | 2024-03-07T23:59:29Z |
| format | Article |
| id | doaj.art-146aaeabf56d4127832f739be858295b |
| institution | Directory Open Access Journal |
| issn | 1608-7070 2588-5774 |
| language | fas |
| last_indexed | 2024-03-07T23:59:29Z |
| publishDate | 2022-06-01 |
| publisher | پژوهشگاه حوزه و دانشگاه |
| record_format | Article |
| series | روش شناسی علوم انسانی |
| spelling | doaj.art-146aaeabf56d4127832f739be858295b2024-02-18T04:58:52Zfasپژوهشگاه حوزه و دانشگاهروش شناسی علوم انسانی1608-70702588-57742022-06-01281117910010.30471/mssh.2022.8106.22661951Application of artificial neural network method in predicting contemporary Iranian family relationshipsMajid Kafi0Seyyede Marziye Shoa Hashemi1Masoud monjezi2Seyed Mohsen Fattahi3Research Institute of Hawzah and UniversityUniversity of Religions and DenominationsTarbiat Modares UniversityUniversity of Religions and ReligionsVirtual social networks play a very important role in social change, especially changes in the structural and emotional relationships of the family. But predicting these changes is very important today. But what method can be used to predict structural changes in the family? This study intends to introduce one of these methods, which is a subset of artificial intelligence, called artificial neural network and as an example to show its effectiveness in predicting the relationships of families affected by virtual social networks. Therefore, the research question is formulated in such a way that by what method or methods can the consequences of the impact of virtual social networks on family relationships be predicted? Since this research is a quantitative research, data collection was done by a questionnaire and the research model was operational. The research model is a fuzzy field statistical model. The result of the research is the prediction of four types of committed, unsuccessful, incompatible and broken families, which were shown on the fuzzy spectrum as follows: Committed family: 75 to 100%; Unsuccessful family: 50 to 75%; Incompatible family 25 to 50 percent and broken family 0 to 25 percent.https://method.rihu.ac.ir/article_1951_f7f1192fe8a7cbcc743cf237345e5f50.pdfartificial intelligenceartificial neural networkemotional relationshipscommitted familyfailed familyincompatible familybroken family |
| spellingShingle | Majid Kafi Seyyede Marziye Shoa Hashemi Masoud monjezi Seyed Mohsen Fattahi Application of artificial neural network method in predicting contemporary Iranian family relationships روش شناسی علوم انسانی artificial intelligence artificial neural network emotional relationships committed family failed family incompatible family broken family |
| title | Application of artificial neural network method in predicting contemporary Iranian family relationships |
| title_full | Application of artificial neural network method in predicting contemporary Iranian family relationships |
| title_fullStr | Application of artificial neural network method in predicting contemporary Iranian family relationships |
| title_full_unstemmed | Application of artificial neural network method in predicting contemporary Iranian family relationships |
| title_short | Application of artificial neural network method in predicting contemporary Iranian family relationships |
| title_sort | application of artificial neural network method in predicting contemporary iranian family relationships |
| topic | artificial intelligence artificial neural network emotional relationships committed family failed family incompatible family broken family |
| url | https://method.rihu.ac.ir/article_1951_f7f1192fe8a7cbcc743cf237345e5f50.pdf |
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