Parameter Identification by Statistical Learning of a Stochastic Dynamical System Modelling a Fishery with price variation
In this short paper we report on an inverse problem for parameter setting of a model used for the modelling of fishing on the West African coast. We compare the solution of this inverse problem by a Neural Network with the more classical algorithms of optimisation and stochastic control. The Neural...
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Format: | Article |
Language: | English |
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Académie des sciences
2020-07-01
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Series: | Comptes Rendus. Mathématique |
Online Access: | https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.5802/crmath.2/ |
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author | Auger, Pierre Pironneau, Olivier |
author_facet | Auger, Pierre Pironneau, Olivier |
author_sort | Auger, Pierre |
collection | DOAJ |
description | In this short paper we report on an inverse problem for parameter setting of a model used for the modelling of fishing on the West African coast. We compare the solution of this inverse problem by a Neural Network with the more classical algorithms of optimisation and stochastic control. The Neural Network does much better. |
first_indexed | 2024-03-11T16:17:12Z |
format | Article |
id | doaj.art-55eb75e065bd462eaec55647aa17dbf9 |
institution | Directory Open Access Journal |
issn | 1778-3569 |
language | English |
last_indexed | 2024-03-11T16:17:12Z |
publishDate | 2020-07-01 |
publisher | Académie des sciences |
record_format | Article |
series | Comptes Rendus. Mathématique |
spelling | doaj.art-55eb75e065bd462eaec55647aa17dbf92023-10-24T14:19:04ZengAcadémie des sciencesComptes Rendus. Mathématique1778-35692020-07-01358324525310.5802/crmath.210.5802/crmath.2Parameter Identification by Statistical Learning of a Stochastic Dynamical System Modelling a Fishery with price variationAuger, Pierre0Pironneau, Olivier1IRD UMI 209, UMMISCO, Sorbonne Université, Bondy, FranceLJLL, Sorbonne Université, Paris 75252, cedex 5, FranceIn this short paper we report on an inverse problem for parameter setting of a model used for the modelling of fishing on the West African coast. We compare the solution of this inverse problem by a Neural Network with the more classical algorithms of optimisation and stochastic control. The Neural Network does much better.https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.5802/crmath.2/ |
spellingShingle | Auger, Pierre Pironneau, Olivier Parameter Identification by Statistical Learning of a Stochastic Dynamical System Modelling a Fishery with price variation Comptes Rendus. Mathématique |
title | Parameter Identification by Statistical Learning of a Stochastic Dynamical System Modelling a Fishery with price variation |
title_full | Parameter Identification by Statistical Learning of a Stochastic Dynamical System Modelling a Fishery with price variation |
title_fullStr | Parameter Identification by Statistical Learning of a Stochastic Dynamical System Modelling a Fishery with price variation |
title_full_unstemmed | Parameter Identification by Statistical Learning of a Stochastic Dynamical System Modelling a Fishery with price variation |
title_short | Parameter Identification by Statistical Learning of a Stochastic Dynamical System Modelling a Fishery with price variation |
title_sort | parameter identification by statistical learning of a stochastic dynamical system modelling a fishery with price variation |
url | https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.5802/crmath.2/ |
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