JOURNAL OF COMPUTERS (JCP)
ISSN : 1796-203X
Volume : 4 Issue : 11 Date : November 2009
Forecasting Fish Stock Recruitment and Planning Optimal Harvesting Strategies by Using Neural Network
Lin Sun, Hongjun Xiao, Shouju Li, and Dequan Yang
Page(s): 1075-1082
Full Text: PDF (597 KB)
Abstract
Recruitment prediction is a key element for management decisions in many fisheries. A new approach using
neural network is developed as a tool to produce a formula for forecasting fish stock recruitment. In order to
deal with the local minimum problem in training neural network with back-propagation algorithm and to
enhance forecasting precision, neural network’s weights are adjusted by optimization algorithm. It is
demonstrated that a well trained artificial neural network reveals an extremely fast convergence and a high
degree of accuracy in the prediction of fish stock recruitment.
Index Terms
neural network, prediction of fish stock recruitment, optimal harvesting strategy, management decision
ISSN : 1796-203X
Volume : 4 Issue : 11 Date : November 2009
Forecasting Fish Stock Recruitment and Planning Optimal Harvesting Strategies by Using Neural Network
Lin Sun, Hongjun Xiao, Shouju Li, and Dequan Yang
Page(s): 1075-1082
Full Text: PDF (597 KB)
Abstract
Recruitment prediction is a key element for management decisions in many fisheries. A new approach using
neural network is developed as a tool to produce a formula for forecasting fish stock recruitment. In order to
deal with the local minimum problem in training neural network with back-propagation algorithm and to
enhance forecasting precision, neural network’s weights are adjusted by optimization algorithm. It is
demonstrated that a well trained artificial neural network reveals an extremely fast convergence and a high
degree of accuracy in the prediction of fish stock recruitment.
Index Terms
neural network, prediction of fish stock recruitment, optimal harvesting strategy, management decision
