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The Research of Examination Paper Generation Based on Index System Metrics and Multi-Objective Strategy

机译:基于指标体系指标和多目标策略的试卷生成研究

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Since the examination paper generated with computer by the algorithms of random and backtracking takes on inferior quality and inefficient, and the question of generating examination paper with computer has the character of multi-ob-jective because of the index system metrics, the genetic algorithm with multi-objective strategy optimization is proposed to solve this problem. Mapping the index system to multi-objective functions and optimizing the computing with multi-objective strategy are employed in the algorithm. The genetic algorithm experiment based on the multi-objective strategy optimization shows that the result has the advantages getting tradeoff between performance and quality, and having the ability to tune the performance and quality to meet the user’s requirements.
机译:由于用随机和回溯算法由计算机生成的试卷质量较差且效率低下,并且由于采用了索引系统指标,因此用计算机生成试卷的问题具有多目标的特点,因此采用遗传算法提出了多目标策略优化来解决这一问题。该算法采用了将索引系统映射到多目标函数,并采用多目标策略对计算进行了优化。基于多目标策略优化的遗传算法实验表明,该结果具有在性能和质量之间进行权衡的优点,并且具有调节性能和质量以满足用户需求的能力。

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