CAJ | 학술논문

个人信用作为社会信用体系建设的重要部分，将其结合现代计算机理论技术来构建个人信用评分模型一直是研究的热点。本文利用前人遗传算法筛选出来的个人信用相关重要属性，并从这些重要属性的3种分类中依类定性地取出部分属性，结合自适应神经模糊推理系统理论(ANFIS)，建立基于遗传算法和AN-FIS的个人信用评分模型。对选取的数据实证分析，并与GA-SVM方法的结果作了比较，试验结果表明该模型只需少量重要属性变量就能够有较好的分类效果。
개인신용작위사회신용체계건설적중요부분，장기결합현대계산궤이론기술래구건개인신용평분모형일직시연구적열점。본문이용전인유전산법사선출래적개인신용상관중요속성，병종저사중요속성적3충분류중의류정성지취출부분속성，결합자괄응신경모호추리계통이론(ANFIS)，건립기우유전산법화AN-FIS적개인신용평분모형。대선취적수거실증분석，병여GA-SVM방법적결과작료비교，시험결과표명해모형지수소량중요속성변량취능구유교호적분류효과。
The integration of personal credit, which is an important part of social credit system, with modern computer science and technology in the process of personal credit scoring model construction has become a hot topic. This paper draws upon the important attribute of personal credit which is selected by previous researcher through genetic algorithm and set out to build a personal credit scoring model that is based on the combination of Genetic Algorithm and ANTFIS. The experimental analysis of data and comparison of the results with GA-SVM show that it has better result than GA-SVM with minimal changes of attribute variables.