EDUCATIONAL TOOL FOR MULTIPLE ATTRIBUTE DECISION MAKING IN BIOMEDICAL ENGINEERING USING FUZZY TOPSIS AND FUZZY VIKOR

M. Ilea, M. Turnea, D. Arotaritei, C. Corciova
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Abstract

Multiple Attribute Decision Making (MADM) is an intensive area of research subject and applications both with many methods applied both in for crisp numbers and in condition of uncertainty, that is, fuzzy framework. In this last case, fuzzy linguistic variables and fuzzy numbers (triangular, trapezoidal or generalized fuzzy) are the along with arithmetic operations are the most common approaches. Depending on distance similarity between fuzzy numbers, the results, no matter the proposed methods, can have slightly different results in intermediary matrices of fuzzy numbers used in calculation. Despite of MADM popularity and usage, in many papers the part that show intermediary results in matrix of fuzzy numbers cover pages and, in this form, it is difficult for the reader to follow all the values in the process of learning these methods. More, if the matrices have higher dimensions and a user (student, e.g.) wants to test some hypothesis, the reproduction of algorithms can be very difficult because of abundance of data. An educational tool is proposed especially for biomedical engineering students, in this stage of development made by two modules: Fuzzy TOPSIS method and fuzzy VIKOR method. Two types of fuzzy numbers are taken into account (triangular fuzzy numbers and trapezoidal fuzzy numbers) and three distance similarity between fuzzy numbers (vertex method, Hausdorff metric and normalized Hamming metric) are three options proposed to used. The user interface (GUI) offers the possibility to visualize all the matrices involved in methods, the steps of algorithms, and also the possibility to select a particular index from matrices.
生物医学工程中基于模糊拓扑和模糊向量的多属性决策教学工具
多属性决策(MADM)是一个研究热点和应用领域,在清晰数字和不确定性条件下,即模糊框架下,应用了许多方法。在最后一种情况下,模糊语言变量和模糊数(三角形、梯形或广义模糊)与算术运算是最常见的方法。根据模糊数之间的距离相似度,无论提出何种方法,计算中使用的模糊数中间矩阵的结果都可能略有不同。尽管MADM很受欢迎和使用,但在许多论文中,模糊数矩阵中表示中间结果的部分占据了页面,在这种形式下,读者在学习这些方法的过程中很难遵循所有的值。此外,如果矩阵具有更高的维度,并且用户(例如学生)想要测试某些假设,则由于数据丰富,算法的再现可能非常困难。本文提出了一种专门针对生物医学工程专业学生的教学工具,在这个发展阶段由两个模块组成:模糊TOPSIS法和模糊VIKOR法。考虑了两种类型的模糊数(三角形模糊数和梯形模糊数),并提出了三种模糊数之间的距离相似度(顶点法、Hausdorff度量和归一化Hamming度量)的选择。用户界面(GUI)提供了可视化方法、算法步骤中涉及的所有矩阵的可能性,还提供了从矩阵中选择特定索引的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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