Complex neutrosophic concept lattice and its applications to air quality analysis

Abstract

a b s t r a c tIn the current year, the precise measurement of uncertainty and fluctuation exists in a complex fuzzy attributes is addressed as computationally and mathematically expensive tasks with regard to its graphical analytics. To deal with this problem the calculus of complex neutrosophic sets are recently introduced to characterize the uncertainty and its changes based on its truth, indeterminacy, and falsity membershipvalue, independently. This given a way to represent the given data sets in form of complex neutrosophic matrix for further analysis towards knowledge processing tasks. In this process, a major problem arises when an expert wants to find some of the interesting patterns in the given complex neutrosophic data sets to solve the particular problem. To resolve this issue, the current paper proposes a method for step by step demonstration to investigate the complex neutrosophic concepts and their graphical structure visualization based on their Lower Neighbors. One of the suitable examples of the proposed method is also given for precise measurement of uncertainty exists in Air Quality Index (AQI) and its pattern at given phase of time.

Granular-based decomposition of complex fuzzy context and its analysis

“…The precise representation of these types of data sets become computationally expensive. This type of periodic data sets and its analysis were first time reported in [18] using a mathematical algebra called as concept lattice. The paper utilizes properties of complex fuzzy set to represent the uncertainty and its fluctuations in the fuzzy attributes using amplitude and phase term, respectively.…”

Identifying Non-Sublattice Equivalence Classes Induced by an Attribute Reduction in FCA

“…The most common redundant data consist of repeated entries, which can be removed without cost, or dependent variables, which can be derived from the independent variables, whose detection is an appealing research topic in many areas dealing with data analysis, such as Formal Concept Analysis (FCA). This mathematical theory was original developed in the 1980s by R. Wille and B. Ganter [1], and it has intensively been studied from a theoretical and applied point of view [2][3][4][5][6][7][8][9][10][11][12]. Two important features of FCA, in which the notion of Galois connection is fundamental [13][14][15][16], is that the information contained in a relational dataset can be described in a hierarchic manner by means of a complete lattice [17] and that dependencies between attributes can be determined [18][19][20][21], which is fundamental to applications.…”

Evaluation of the Economic Relationships on the Basis of Statistical Decision-Making in Complex Neutrosophic Environment

“…Furthermore, Gulistan et al [41] introduced the CN subsemigroups and ideals. Ali and Mahmood [42], Al-Quran and Hassan [43], Manna et al [44], and Dat et al [45] applied the CNSs for decision-making, and Singh [46] used CNSs to analyze the air quality. Klir and Folger [47] presented the concept of crisp relations (CRs) that are based on the crisp set theory.…”