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The Application of Genetic Algorithm into Intelligent Test Paper
Author: LiangXiaoLi
Tutor: YinDaLi
School: Changchun University of Science and Technology
Course: Computer Software and Theory
Keywords: Genetic Algorithms Intelligent Test Mathematical model Arithmetic crossover
CLC: TP18
Type: Master's thesis
Year: 2010
Downloads: 97
Quote: 2
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Abstract
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With the computer technology and artificial intelligence technology, test paper studies the problem being more and more attention . Intelligent Test is a problem under certain constraints multi-objective optimization problem parameters , test paper depends entirely on the efficiency and quality of the pumping test database and algorithm design problems . Algorithmic traditional slow with test paper , test papers is not high quality defects. To address this problem, this paper focuses on the Genetic Algorithm in Composing Test Paper , proposed an improved genetic algorithm, effectively avoid the simple genetic algorithm slow convergence and local convergence defects and improve the efficiency and quality of the test paper . A detailed analysis of the various constraints papers , the paper established a sub- title , difficulty, discrimination and knowledge variables test paper model coverage , on the basis of the design of a measure to weight constraints important degree of fitness function ; improved genetic algorithm uses real number coding scheme , the value of direct questions genes represented by numbers, to avoid the decoding process of loss of time ; paper also introduces a new arithmetic crossover strategy to increase search space of the algorithm to improve the quality of test paper ; final preparation program improved genetic algorithm, and apply it to the test system , by simulation experiments confirmed : Improved genetic algorithm genetic algebra, test Paper time , paper quality , the number of successes with greater advantages.
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