الفهرس 
Title : A Computational Intelligent Approach for Managing Fish Farming
AbstractOnly 14 pages are availabe for public view
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Abstract
Fuzzy logic as a soft computing technique can handle uncertainty and approximate reasoning in a flexible and reliable fashion. It is more accurate in modeling uncertainty compared with the traditional methods. Fuzzy queries have appeared to cope with the necessity to soften the Boolean logic in database queries; the query returns the results with degrees of matching membership values rather than crisp values true or false. A fuzzy query system is an interface to users to get information from database using natural language sentences. Generally, in some spatial sites, water quality changes in its parameters like dissolved oxygen, acidity and temperature.These ongoing changes have more impact on fish farming. In consequence, some spatial sites do not become suitable for fish farming because of the bad water quality. Instead, fish farming becomes more suitable at other new discovered or adjusted spatial sites.This thesis provides a fuzzy-based approach for selecting the suitable water quality spatial sites for fish farming respecting its dissolved oxygen, acidity and temperature. Besides, the thesis introduces the required enhancement percent for the unsuitable sites.The proposed approach consists of five phases.The first phase considers preparing the water quality parameters of spatial sites database and the required water quality for fish farming.The second phase defines a set of fuzzy membership functions for defining the membership degree of sites water quality suitable for fish farming. In the third phase, the approach performs fuzzy query on the water sites to fetch the suitable sites for fish farming. The fourth phase performs clustering of sites according to their suitability degrees.The last phase finds the suitability effective parameters and the percent of the required enhancement for the unsuitable sites