An Enhancement Edas Method Based on Prospect Theory

With the continuous development of mobile Internet and educational technology, the deep integration of education and Internet has a great impact on the education concept and teaching mode. The mixed teaching based on Rain Classroom is the specific application of new educational technology in the teaching of Internet plus education. Most of the students in ethnic universities come from the central and western ethnic regions. In addition, the evaluation of blended classroom teaching reform effect is looked as the classical multiple attribute decision making (MADM). We extend the dual MSM (DMSM) operator with fuzzy number intuitionistic fuzzy numbers (FNIFNs) to build the fuzzy number intuitionistic fuzzy dual MSM (FNIFDMSM) operator and fuzzy number intuitionistic fuzzy weighted DMSM (FNIFWDMSM) equation in this study. A few MADM operators are built with FNIFWDMSM operator. Finally, taking blended classroom teaching reform effect evaluation as an useful example, this paper illustrates the depicted approach.

Section: Introductionmentioning

confidence: 99%

Method for Fuzzy Number Intuitionistic Fuzzy Multiple Attribute Decision Making and Its Application to Blended Classroom Teaching Reform Effect Evaluation

Sun

2022

“…Step 5. Calculate the SVNN composite distance matrix (SVNNCDM): Firstly, the distance of each alternative from other given alternatives is obtained through (9):…”

Section: Svnn-taxonomy Methods For Magdm With Critic Weightmentioning

confidence: 99%

“…Decision-making is a very common phenomenon which ranges from personal clothing, housing, and transportation to national policy formulation and is closely related to people's lives [1][2][3][4][5]. Among them, multi-attribute decisionmaking (MADM) means that under many di erent requirements and criteria, the plan to be selected needs to be evaluated by decision-makers or corresponding experts and scholars, and the most suitable decision-making plan isnally selected through scienti c methods [6][7][8][9][10]. As an important part of modern decision science, multi-attribute decision-making has been favored by many scholars and experts and its methods and theories have been applied to many practical elds such as politics, business, environment, and energy [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

An Integrated Taxonomy Method Using Single-Valued Neutrosophic Number MAGDM for Evaluating the Physical Education Teaching Quality in Colleges and Universities

Yang

Liu

2022

Before the advent of the new era, my country has completed the popularization of higher education, and the country has gradually begun to pay attention to the quality of higher education. Under the background of Healthy China, the quality of physical education teaching in colleges and universities has become a hot topic of social concern. The quality of physical education teaching in colleges and universities directly determines the quality of physical education talents. A reasonable, complete, and scientific evaluation system of physical education teaching quality in colleges and universities is an effective measure to improve the quality of physical education teaching and the training of physical education talents. The physical education teaching quality evaluation in colleges and universities is frequently viewed as the multiple attribute group decision-making (MAGDM) issue. In such paper, taxonomy method is designed for solving the MAGDM under single-valued neutrosophic sets (SVNSs). First, the score function of SVNSs and criteria importance through intercriteria correlation (CRITIC) method is used to derive the attribute weights. Second, then, the optimal choice is obtained through calculating the smallest single-valued neutrosophic number development attribute values from the single-valued neutrosophic number positive ideal solution (SVNNPIS). Finally, a numerical example for physical education teaching quality evaluation in colleges and universities is given to illustrate the built method.

“…EDAS is an MCDM method that evaluates the alternatives (i.e., features) using two measures: (i) positive distance from average (PDA) and (ii) negative distance from average (NDA) [70][71][72]. e best alternative has the highest PDA value or lowest NDA value.…”

Section: Evaluation Based On Distance From Average Solution (Edas) Me...mentioning

confidence: 99%

Ensemble Feature Selection in Binary Machine Learning Classification: A Novel Application of the Evaluation Based on Distance from Average Solution (EDAS) Method

Abellana

Roxas

Lao

et al. 2022

Combining filters in an ensemble to improve feature selection performance is a growing field in the literature. Current techniques, however, are focused on approaches that suffer from drawbacks such as sensitivity to skewed distribution, among others. To address this gap, this paper investigates the applicability of multiple criteria decision-making in ensemble feature selection. This paper adopts the Evaluation based on Distance from Average Solution (EDAS) method due to its many familiar elements to the feature selection community. An experiment was performed on six datasets and a control group. The paper uses the six datasets as levels of the blocking factor. A negative control group (i.e., no feature selection) was adopted to compare with the proposed algorithm. Results show that the proposed ensemble FS algorithm was able to reduce the dataset without compromising the performance of the classifier. The findings in this study would contribute to the literature in several ways. First, the paper is one of the few works to demonstrate how MCDM can be used in feature selection with promising results. Second, this paper is one of the few works to demonstrate the significance of including datasets as levels of a blocking factor when performing significance testing. Finally, this paper is the first to demonstrate the applicability of EDAS as an ensemble FS algorithm. As such, the findings in this paper could spark the cross-fertilization of feature selection and MCDM.