Download Free Neutrosophic Reducible Weighted Maclaurin Symmetric Mean For Undergraduate Teaching Audit And Evaluation Book in PDF and EPUB Free Download. You can read online Neutrosophic Reducible Weighted Maclaurin Symmetric Mean For Undergraduate Teaching Audit And Evaluation and write the review.

The undergraduate teaching audit and evaluation (UTAE) is critically important for university to promote the establishment of a quality assurance system and improve the quality of teaching. In considering the case of UTAE, the essential question that arises strong ambiguity and interaction. The Maclaurin symmetric mean (MSM), as a significant information integration tool, can seize the interrelation among multiple input values more effectively.
This book presents the proceedings of the 8th International Workshop on Soft Computing Applications, SOFA 2018, held on 13–15 September 2018 in Arad, Romania. The workshop was organized by Aurel Vlaicu University of Arad, in conjunction with the Institute of Computer Science, Iasi Branch of the Romanian Academy, IEEE Romanian Section, Romanian Society of Control Engineering and Technical Informatics – Arad Section, General Association of Engineers in Romania – Arad Section and BTM Resources Arad. The papers included in these proceedings, published post-conference, cover the research including Knowledge-Based Technologies for Web Applications, Cloud Computing, Security Algorithms and Computer Networks, Business Process Management, Computational Intelligence in Education and Modelling and Applications in Textiles and many other areas related to the Soft Computing. The book is directed to professors, researchers, and graduate students in area of soft computing techniques and applications.
“Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc.
As a variation of fuzzy sets and intuitionistic fuzzy sets, neutrosophic sets have been developed to represent uncertain, imprecise, incomplete and inconsistent information that exists in the real world. Simplified neutrosophic sets (SNSs) have been proposed for the main purpose of addressing issues with a set of specific numbers. However, there are certain problems regarding the existing operations of SNSs, as well as their aggregation operators and the comparison methods. Therefore, this paper defines the novel operations of simplified neutrosophic numbers (SNNs) and develops a comparison method based on the related research of intuitionistic fuzzy numbers. On the basis of these operations and the comparison method, some SNN aggregation operators are proposed. Additionally, an approach for multi-criteria group decision-making (MCGDM) problems is explored by applying these aggregation operators. Finally, an example to illustrate the applicability of the proposed method is provided and a comparison with some other methods is made.
In this paper one generalizes the intuitionistic fuzzy set (IFS), paraconsistent set, and intuitionistic set to the neutrosophic set (NS). Many examples are presented. Distinctions between NS and IFS are underlined.
The Internet of Medical Things (IoMT) is a global infrastructure composing of plentiful applications and medical devices that are interconnected by ICT. In considering the problem of the IoMT industry evaluation, the requisite issue that concerns strong interaction and incertitude. The Maclaurin symmetric mean (MSM), as a resultful information concordant instrument, can capture the interrelation among multiple arguments more efciently. The abundance of the weighted MSMs has been presented to manage the different uncertain information aggregation issues by reason that the attribute variables are frequently diverse. However, these existing weighted form of MSM operators fail to possess the fundamental properties of idempotency and reducibility. To solve the above issues, we explore the interval neutrosophic reducible weighted MSM (INRWMSM) operator and the interval neutrosophic reducible weighted dual MSM (INRWDMSM) operator. Moreover, momentous properties and some special cases of the INRWMSM and INRWDMSM operators are discussed in detail.
The aim of this paper is to introduce some new operators for aggregating single-valued neutrosophic (SVN) information and to apply them to solve the multi-criteria decision-making (MCDM) problems.
In this paper, we introduced a new concept of single valued neutrosophic graph (SVNG) known as constant single valued neutrosophic graph (CSVNG). Basically, SVNG is a generalization of intuitionistic fuzzy graph (IFG). More specifically, we described and explored somegraph theoretic ideas related to the introduced concepts of CSVNG. An application of CSVNG in a Wi-Fi network system is discussed and a comparison of CSVNG with constant IFG is established showing the worth of the proposed work. Further, several terms like constant function and totally constant function are investigated in the frame-work of CSVNG and their characteristics are studied.
As a generalization of fuzzy sets and intuitionistic fuzzy sets, neutrosophic sets have been developed to represent uncertain, imprecise, incomplete, and inconsistent information existing in the real world. And interval neutrosophic sets (INSs) have been proposed exactly to address issues with a set of numbers in the real unit interval, not just a specific number.However, there are fewer reliable operations for INSs, as well as the INS aggregation operators and decisionmakingmethod. For this purpose, the operations for INSs are defined and a comparison approach is put forward based on the related research of interval valued intuitionistic fuzzy sets (IVIFSs) in this paper. On the basis of the operations and comparison approach, two interval neutrosophic number aggregation operators are developed. Then, amethod formulticriteria decisionmaking problems is explored applying the aggregation operators. In addition, an example is provided to illustrate the application of the proposed method.