A Web-Based Egg-Quality Expert Advisory System using Rule Based and Ant Colony (ACO) Optimization Algorithms
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Abstract
This paper deals with the development of Web based online expert systems using Evolutionary Algorithms. An expert system is a
computer application that performs a task that would otherwise be performed by a human expert. Here one of the evolutionary algorithms (ACO
Algorithm) is considered to find a good match of symptoms in the database. In the present paper, Ant Colony Optimization1 (ACO) algorithm
has been taken as the base and the concept of optimization is included, so that the new algorithm mainly focuses on the determination of the
quality of eggs in the poultry farms. At first, the symptoms provided by the user are processed by a rule based expert system for identifying the
quality of the eggs. If the rules required for processing the data by the above are not present in the database, then the system automatically calls
the machine learning algorithm technique. As a whole, the system results good optimized solution for recognizing the quality and viruses if any
affected to eggs in poultry farms. And corresponding treatments to the viruses may also be suggested to the users. This expert system is designed
with JSP as front end and MySQL as backend.
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Keywords: Expert Systems, Rule Based System, Ant Colony Optimization Algorithm Optimization, Eggs in poultry farms, JSP, MySQL.
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