A proposed model to estimate the growth of the fishery populations by expert system
Keywords:
Fuzzy logic, Fuzzy inferencing unit, MatlabAbstract
When studying the growth of fishery populations, the question of validation of growth parameter estimates often arises due to the lack of reliability of some of the methods used in obtaining such estimates. It has been suggested a model, which aims to find an advanced scientific model to estimate the growth of the fishery populations by artificial intelligence technologies such as fuzzy logic and thus determine the ability to make decisions regarding this growth. An expert system has been built that contains inference rules which consist of four input variables (VBGF parameter, K; age at recruitment, Tr; natural mortality rate, M; exploitation, E) for each species. The research has highlighted to important results:
- The proposed model depends on a strong inference system in which all cases studied for four input variables were discussed and It could be applied to all fish species, which helps to increase opportunities to improve fishing management and sustainability.
- A high degree of reliability of the model to estimate the growth of the fishery populations compared to the Musick criterion, which is based only on the value of the growth factor (K) for Bertalanffy in assessing fisheries productivity.
