Near the entire university faculty directors must select some qualified professors for respected courses in each academic semester. In this sense, factors such as teaching experience, academic training, competition, etc. are considered. This work is usually done by experts, such as faculty directors, which is time consuming. Up to now, several semi-automatic systems have been proposed to assist heads. In this article, a fully automatic rule-based expert system is developed. The proposed expert system consists of three main stages. First, the knowledge of human experts is entered and designed as a decision tree. In the second step, an expert system is designed based on the provided rules of the generated decision tree. In the third step, an algorithm is proposed to weight the results of the tree based on the quality of the experts. To improve the performance of the expert system, a majority voting algorithm is developed as a post-process step to select the qualified trainer who satisfies the most expert decision tree for each course. The quality of the proposed expert system is evaluated using real data from Iranian universities. The calculated accuracy rate is 85.55, demonstrating the robustness and accuracy of the proposed system. The proposed system has little computational complexity compared to related efficient works. Also, simple implementation and transparent box are other features of the proposed system.
翻译:整个大学校长必须挑选一些合格的教授,在每个学期的受人尊敬的课程中挑选一些合格的教授。从这个意义上讲,要考虑到教学经验、学术培训、竞争等因素。这项工作通常由专家进行,例如教员主任等专家进行,这是耗时的。到目前为止,已提议采用若干半自动系统来协助负责人。在本条中,开发了一个完全自动的有章可循的专家系统。拟议的专家系统由三个主要阶段组成。首先,人类专家的知识被输入,并设计成决策树。第二步,专家系统的设计以所产生的决策树的既定规则为基础。第三步,根据专家的质量提出算法,对树的成果进行加权。为了改进专家系统的业绩,将制定一个多数投票算法,作为后期步骤,挑选出一个符合每项课程最专家决策的合格教员。拟议的专家系统的质量是用伊朗大学的真实数据进行评估。计算出的准确率为85.55,表明所拟议的系统是否健全和准确。提议的系统与相关的高效工作相比,拟议的系统在计算上没有多大的复杂度。提议的系统与相关的透明性,拟议的系统是其他的简单和透明性。