Research On Intelligent Examination System Based On Adaptive Genetic Algorithms

The intelligent test system is in the last few years along with the rapid development in network technique but newly arisen research topics. The intelligent test system can lessen the repeating work of teachers, and improve the efficiency. The intelligent paper forming function can improve the quality of test papers and increase the objectivity of test. This article embarked from the intelligent examination actual demand, has analyzed main function of the intelligent examination system, proposed programme Intelligent test system design.This thesis focuses on a intelligent algorithm of paper construction. Test paper construction is a multi-object restrict optimization problem. Because of its global search, randomness, the better coding and a high degree of parallelism, Genetic Algorithm is very conducive to solving such problems. So this thesis uses genetic algorithms to solve the problem. This thesis analyses requirements of test paper construction, proposals the theory model of intelligent construction system problems,uses the dynamic adaptive parameter adjustment method to solve the problem of "Premature convergence" in view of algorithm, implements adaptive genetic algorithm solution of the test paper construction, and optimizes algorithm based on natural system. The problem of test questions repeatability has been solved, it effectively avoids similar papers Generation. Experiment and actual system prove that the algorithm has more accurate performance and the system has better practicability.In this foundation, taking the ShenZhen Electronic Technical Schools education institute distance earning project as the background, this thesis introduces multi-layered model based on .net B/S pattern, discusses the intelligent examination system design and implementation in use of the popularASP.NET technology and SQL SERVER DBMS.