Cross-entropy method for interval-valued neutrosophic number multiple attribute decision making for education quality management evaluation in higher education institutions

Author:

Jia Xiaoying1

Affiliation:

1. School of Automation, Huaiyin Institute of Technology, Huai’an, Jiangsu, China

Abstract

Under the premise of today’s socialist modernization construction, the development and progress of the country require more outstanding talents such as aspiring youth and intellectuals to participate, which puts forward higher requirements for education quality indicators and various aspects of operation. As the main institution and environment for implementing educational activities, the effectiveness of school management organization has a direct impact and even a decisive role on the quality of education. Therefore, how to improve the quality management of school education has become a hot topic in the education industry. The education quality management evaluation in higher education institutions is viewed as the multiple-attribute decision-making (MADM) issue. In this paper, the interval-valued neutrosophic number cross-entropy (IVNN-CE) technique is built under interval-valued neutrosophic sets (IVNSs) based on the traditional cross-entropy technique. Then, combine traditional cross-entropy technique with IVNSs, the IVNN-CE technique is constructed for MADM under IVNSs. Finally, the numerical example for education quality management evaluation in higher education institutions was constructed and some comparisons is employed to verify advantages of IVNN-CE technique. The main contribution of this paper is constructed: (1) the cross-entropy model is extended to IVNSs; (1) the CRITIC technique is employed to construct the attribute weights under IVNSs; (3) the IVNN-CE technique is constructed to manage the MADM under IVNSs; (4) a case study about education quality management evaluation in higher education institutions is constructed to show the built technique; (5) some comparative algorithms are constructed to verify the rationality of IVNN-CE technique.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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