一种粒子群模糊专家系统:作为用NOET方法确定博士级验收的辅助

Seyed Muhammad Hossein Mousavi, S. Mirinezhad, Mehrdad Shafaei Mosleh, M. Dezfoulian
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引用次数: 4

摘要

智能决策系统是人类专家辅助决策的有效工具,是各种自动决策领域专家的理想替代方案。在教育、农业、工业、渔业、畜牧业等领域使用这种系统,可以减少人力错误或减少对人力的需求;另一方面,它可以提高服务的质量和速度。博士学位甚至硕士学位的面试,由于分数对考生的高度敏感性,因此非常重要。因此,创建一个系统来存储这些分数,并在有大量候选人时推断结果可能是有益的。在本文中,该专家系统具有教育用途,并根据(国家教育考试组织)NOET措施对博士候选人在考试和面试中的录取或不录取概率进行分类,并对候选人的科学水平进行估计。提出的模糊专家系统利用粒子群优化(PSO)进化算法来指定每个变量的得分,并最终确定候选对象的最终条件。所获得的评价结果证明了模糊专家系统的功能性。该系统也能够很好地对类似的教育案例进行评分,以指定接受程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A PSO fuzzy-expert system: As an assistant for specifying the acceptance by NOET measures, at PH.D level
The intelligent decision making systems are useful tools for the assistance of human expert, and or as a perfect alternative for expert in a variety of auto-decision making fields. The use of such systems in education, agriculture, industry, fishery, animal husbandry etc., can decrease manpower errors or need of it; In the other hand, it can increase the quality and the pace of service giving. The interview at the PH.D level or even Master's degree, due to the high sensitivity in scoring to the candidates, is of high importance. Therefore, creating a system for storing these scores, and inferring the results can be beneficial when there is a large number of candidates. In this paper, the expert system has an educational use, and classifies the probability of acceptance or unacceptance of PH.D candidates in the exam and interview, based on the (National Organization of Educational Testing) NOET measures, also estimates scientific level of candidates. The proposed fuzzy-expert system takes advantage of the particle swarm optimization (PSO) evolutionary algorithm to specifying the score of each variable, and eventually the final condition of the candidate. The acquired results of evaluating the fuzzy-expert system proves its functionality. This system is also able to function well in scoring similar educational cases to specify acceptance.
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