There are many practical decision-making problems in people’s lives, but the information given by decision makers (DMs) is often unclear and how to describe this information is of critical importance.

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 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.

In this article, we first define some operational laws for interval neutrosophic numbers (INNs) based on Dombi TN and TCN and discuss several desirable properties of these operational rules. Secondly, we extend the PBM operator based on Dombi operations to develop an interval-neutrosophic Dombi PBM (INDPBM) operator, an interval-neutrosophic weighted Dombi PBM (INWDPBM) operator, an interval-neutrosophic Dombi power geometric Bonferroni mean (INDPGBM) operator and an interval-neutrosophic weighted Dombi power geometric Bonferroni mean (INWDPGBM) operator, and discuss several properties of these aggregation operators.

Linguistic neutrosophic numbers (LNNs) can easily describe the incomplete and indeterminate information by the truth, indeterminacy, and falsity linguistic variables (LVs), and the Hamy mean (HM) operator is a good tool to deal with multiple attribute group decision making (MAGDM) problems because it can capture the interrelationship among the multi-input arguments.

In order to take into account quantitative and qualitative information in real complex decision making issue, a multiple-valued neutrosophic uncertain linguistic set (MVNULS) is initially proposed, which includes the uncertain linguistic part and the multiple-valued neutrosophic set (MVNS). Consequently, it has the advantages of them in expressing evaluation information.

This Special Issue presents original research papers that report on state-of-the-art and recent advancements in neutrosophic sets and logic in soft computing, artificial intelligence, big and small data mining, decision making problems, and practical achievements.