On Artificial Neural Networks Approach With New Cost Functions
| dc.contributor.author | Jafarian, Ahmad | |
| dc.contributor.author | Nia, Safa Measoomy | |
| dc.contributor.author | Golmankhaneh, Alireza Khalili | |
| dc.contributor.author | Baleanu, Dumitru | |
| dc.date.accessioned | 2020-03-17T13:30:08Z | |
| dc.date.accessioned | 2025-09-18T12:04:38Z | |
| dc.date.available | 2020-03-17T13:30:08Z | |
| dc.date.available | 2025-09-18T12:04:38Z | |
| dc.date.issued | 2018 | |
| dc.description | Khalili Golmankhaneh, Alireza/0000-0002-5008-0163 | en_US |
| dc.description.abstract | In this manuscript, the artificial neural networks approach involving generalized sigmoid function as a cost function, and three-layered feed-forward architecture is considered as an iterative scheme for solving linear fractional order ordinary differential equations. The supervised back-propagation type learning algorithm based on the gradient descent method, is able to approximate this a problem on a given arbitrary interval to any desired degree of accuracy. To be more precise, some test problems are also given with the comparison to the simulation and numerical results given by another usual method. (C) 2018 Elsevier Inc. All rights reserved. | en_US |
| dc.identifier.citation | Jafarian, Ahmad...et al. (2018). "On artificial neural networks approach with new cost functions", Applied Mathematics and Computation, Vol. 339, pp. 546-555. | en_US |
| dc.identifier.doi | 10.1016/j.amc.2018.07.053 | |
| dc.identifier.issn | 0096-3003 | |
| dc.identifier.issn | 1873-5649 | |
| dc.identifier.scopus | 2-s2.0-85051662269 | |
| dc.identifier.uri | https://doi.org/10.1016/j.amc.2018.07.053 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12416/10404 | |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier Science inc | en_US |
| dc.relation.ispartof | Applied Mathematics and Computation | |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Fractional Order Ordinary Differential Equation | en_US |
| dc.subject | Artificial Neural Networks Approach | en_US |
| dc.subject | Least Mean Squares Cost Function | en_US |
| dc.subject | Supervised Back-Propagation Learning Algorithm | en_US |
| dc.title | On Artificial Neural Networks Approach With New Cost Functions | en_US |
| dc.title | On artificial neural networks approach with new cost functions | tr_TR |
| dc.type | Article | en_US |
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| gdc.author.id | Khalili Golmankhaneh, Alireza/0000-0002-5008-0163 | |
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| gdc.author.wosid | Baleanu, Dumitru/B-9936-2012 | |
| gdc.author.wosid | Khalili Golmankhaneh, Alireza/L-1554-2013 | |
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| gdc.description.department | Çankaya University | en_US |
| gdc.description.departmenttemp | [Jafarian, Ahmad; Nia, Safa Measoomy] Islamic Azad Univ, Dept Math, Urmia Branch, Orumiyeh, Iran; [Golmankhaneh, Alireza Khalili] Islamic Azad Univ, Young Researchers & Elite Club, Urmia Branch, Orumiyeh, Iran; [Baleanu, Dumitru] Cankaya Univ, Dept Math, TR-06530 Ankara, Turkey; [Baleanu, Dumitru] Inst Space Sci, MG-23, R-76900 Bucharest, Romania | en_US |
| gdc.description.endpage | 555 | en_US |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
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| gdc.description.startpage | 546 | en_US |
| gdc.description.volume | 339 | en_US |
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| gdc.oaire.keywords | least mean squares cost function | |
| gdc.oaire.keywords | fractional-order ordinary differential equation | |
| gdc.oaire.keywords | Linear ordinary differential equations and systems | |
| gdc.oaire.keywords | Pattern recognition, speech recognition | |
| gdc.oaire.keywords | supervised back-propagation learning algorithm | |
| gdc.oaire.keywords | artificial neural networks approach | |
| gdc.oaire.keywords | Fractional ordinary differential equations | |
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| gdc.virtual.author | Baleanu, Dumitru | |
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