CAJ | 학술논문

主要研究了网络考试系统设计中利用遗传算法进行智能组卷的问题．首先根据用户对组卷的要求，利用遗传算法对组卷所需的约束条件设置各项指标，利用矩阵理论建立有利于遗传算子进行组合交叉和变异的数学模型；再针对组卷问题中的一个重要约束条件——试卷的难度指标，采用模糊数学方法和项目反应理论对试题库中每一小题进行综合评价试题难度的数学建模，以准确确定每道小题的试题难度系数，最终为实现遗传算法全局寻优和智能搜索奠定基础．
주요연구료망락고시계통설계중이용유전산법진행지능조권적문제．수선근거용호대조권적요구，이용유전산법대조권소수적약속조건설치각항지표，이용구진이론건립유리우유전산자진행조합교차화변이적수학모형；재침대조권문제중적일개중요약속조건——시권적난도지표，채용모호수학방법화항목반응이론대시제고중매일소제진행종합평개시제난도적수학건모，이준학학정매도소제적시제난도계수，최종위실현유전산법전국심우화지능수색전정기출．
The present paper mainly studies the intelligent test composition by using genetic algorithms in network test system design. In the first place, the indicators are set according to user requirements on the test paper and the constraints by using genetic algorithm to carry out the test paper, using matrix theory to create the mathematical model that enabled genetic operator to crossover combination and mutation, and then one of the major constraints the difficulty of indicators for Test Paper is constructed, using fuzzy comprehen sive evaluation of the mathematical methods and item response theory to each question in the test database to evaluate difficulty of mathematical modeling in order to accurately decide the difficulty coefficient of each item, and ultimately lay the foundation for the realization of the genetic algorithm global optimization and in telligent search.