Solving Capelin Time Series Ecosystem Problem using Hybrid Artificial Neural Networks- Genetic Algorithms Model

The Capelin stock in the Barents Sea is the largest in the world. It maintained a fishery with annual catches of up to 3 million tons. The Capelin stock problem has an impact in fish stock development. In this paper, the stock prediction problem of the Barents Sea capelin is attacked using Artificia...

Full description

Bibliographic Details
Main Authors: Karam M. Eghnam, Sulieman Bani-ahmad, Alaa F. Sheta
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Subjects:
Capelin stock
Neural Networks
Genetic Algorithm
Ecosystem
Barents Sea
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.206.3983
http://www.ijcaonline.org/volume19/number2/pxc3873046.pdf
id ftciteseerx:oai:CiteSeerX.psu:10.1.1.206.3983
record_format openpolar
spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.206.3983 2023-05-15T15:38:29+02:00 Solving Capelin Time Series Ecosystem Problem using Hybrid Artificial Neural Networks- Genetic Algorithms Model Karam M. Eghnam Sulieman Bani-ahmad Alaa F. Sheta The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.206.3983 http://www.ijcaonline.org/volume19/number2/pxc3873046.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.206.3983 http://www.ijcaonline.org/volume19/number2/pxc3873046.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.ijcaonline.org/volume19/number2/pxc3873046.pdf Capelin stock Neural Networks Genetic Algorithm Ecosystem text ftciteseerx 2016-01-07T17:39:25Z The Capelin stock in the Barents Sea is the largest in the world. It maintained a fishery with annual catches of up to 3 million tons. The Capelin stock problem has an impact in fish stock development. In this paper, the stock prediction problem of the Barents Sea capelin is attacked using Artificial Neural Network (ANNs) and Multiple Linear model Regression (MLR) model. The weights of ANNs are adapted using the Genetic Algorithm (GA).The models are compared against each other and empirical work has shown that the ANN-GA model can have better overall accuracy over (MLR). It performs 21 % over MLR model. Text Barents Sea Unknown Barents Sea
institution Open Polar
collection Unknown
op_collection_id ftciteseerx
language English
topic Capelin stock
Neural Networks
Genetic Algorithm
Ecosystem
spellingShingle Capelin stock
Neural Networks
Genetic Algorithm
Ecosystem
Karam M. Eghnam
Sulieman Bani-ahmad
Alaa F. Sheta
Solving Capelin Time Series Ecosystem Problem using Hybrid Artificial Neural Networks- Genetic Algorithms Model
topic_facet Capelin stock
Neural Networks
Genetic Algorithm
Ecosystem
description The Capelin stock in the Barents Sea is the largest in the world. It maintained a fishery with annual catches of up to 3 million tons. The Capelin stock problem has an impact in fish stock development. In this paper, the stock prediction problem of the Barents Sea capelin is attacked using Artificial Neural Network (ANNs) and Multiple Linear model Regression (MLR) model. The weights of ANNs are adapted using the Genetic Algorithm (GA).The models are compared against each other and empirical work has shown that the ANN-GA model can have better overall accuracy over (MLR). It performs 21 % over MLR model.
author2 The Pennsylvania State University CiteSeerX Archives
format Text
author Karam M. Eghnam
Sulieman Bani-ahmad
Alaa F. Sheta
author_facet Karam M. Eghnam
Sulieman Bani-ahmad
Alaa F. Sheta
author_sort Karam M. Eghnam
title Solving Capelin Time Series Ecosystem Problem using Hybrid Artificial Neural Networks- Genetic Algorithms Model
title_short Solving Capelin Time Series Ecosystem Problem using Hybrid Artificial Neural Networks- Genetic Algorithms Model
title_full Solving Capelin Time Series Ecosystem Problem using Hybrid Artificial Neural Networks- Genetic Algorithms Model
title_fullStr Solving Capelin Time Series Ecosystem Problem using Hybrid Artificial Neural Networks- Genetic Algorithms Model
title_full_unstemmed Solving Capelin Time Series Ecosystem Problem using Hybrid Artificial Neural Networks- Genetic Algorithms Model
title_sort solving capelin time series ecosystem problem using hybrid artificial neural networks- genetic algorithms model
url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.206.3983
http://www.ijcaonline.org/volume19/number2/pxc3873046.pdf
geographic Barents Sea
geographic_facet Barents Sea
genre Barents Sea
genre_facet Barents Sea
op_source http://www.ijcaonline.org/volume19/number2/pxc3873046.pdf
op_relation http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.206.3983
http://www.ijcaonline.org/volume19/number2/pxc3873046.pdf
op_rights Metadata may be used without restrictions as long as the oai identifier remains attached to it.
_version_ 1766369457566908416

Similar Items