This paper explores the use of the optimization procedures in SAS/OR software with application to the ordered weighted averaging (OWA) operators of decision-making. OWA was originally introduced by Yager (1988) has gained much interest among researchers, hence many applications in the areas of decision making, expert systems, data mining, approximate reasoning, fuzzy system and control have bee...

In this paper, we first review existing fuzzy extensions of the dominance-based rough set approach (DRSA), and advance theory considering additional properties. Moreover, examine application Ordered Weighted Average (OWA) operators to DRSA. OWA have shown a lot potential in handling outliers noisy data decision tables, when they are combined with indiscernibility-based (IRSA). We theoretical pr...

Distortion risk measures summarize the risk of a loss distribution by means of a single value. In fuzzy systems, the Ordered Weighted Averaging (OWA) and Weighted Ordered Weighted Averaging (WOWA) operators are used to aggregate a large number of fuzzy rules into a single value. We show that these concepts can be derived from the Choquet integral, and then the mathematical relationship between ...

The assessment of goods quality using experts is costly task in addition to their often unavailability. In this paper, we present a new method for ranking physical features of consumer goods according to their relevancy to multiple evaluators’ perception at different levels and selecting the most important ones for quality characterization. The main contribution of the paper is combining of fuz...

Fuzzy rough set theory can be used as a tool for dealing with inconsistent data when there is gradual notion of indiscernibility between objects. It does this by providing lower and upper approximations concepts. In classical fuzzy sets, the are determined using minimum maximum operators, respectively. This undesirable machine learning applications, since it makes these sensitive to outlying sa...

Fuzzy quantifiers, i.e. operators intended to provide a numerical interpretation of natural language (NL) quantifiers like ‘almost all’, are valuable tools for image processing, in particular to express accumulative (second order) properties of fuzzy image regions. However, approaches to fuzzy quantification will unfold their full potential only if the proposed operators capture the meaning of ...

Abstract An IFS is suitable way to deal with uncertainty, but operators on it are complex in computation even though they work well. This study presents a C-OWA operator-based method to make aggregation over intuitionistic fuzzy information more easy and convenient, and then applies it to complicated decision making under uncertainty. IFNs or IIFNs are transformed into intervals which are easy ...

We propose a least absolute deviation model for obtaining OWA operator weights: Minimize ∑i=n−1 i=1 |wi − wi−1| subject to orness(W ) = ∑n i=1 n−i n−1wi = α, 0 ≤ α ≤ 1, w1 + · · ·+ wn = 1, 0 ≤ wi, i = 1, · · · , n. Recently, the extended minimax disparity problem was proved by Hong [Fuzzy Sets and Systems, 168 (2011) 35-46]. In this paper, we investigated the equivalence of the solutions for th...

In this paper we propose an extension of the wellknown OWA functions introduced by Yager to interval-valued (IVFS) and Atanassov’s intuitionistic (AIFS) fuzzy set theory. We first extend the arithmetic and the quasi-arithmetic mean using the arithmetic operators in IVFS and AIFS theory and investigate under which conditions these means are idempotent. Since on the unit interval the construction...

The Nearest Neighbor (NN) algorithm is a well-known and effective classification algorithm. Prototype Selection (PS), which provides NN with a good training set to pick its neighbors from, is an important topic as NN is highly susceptible to noisy data. Accurate state-of-the-art PS methods are generally slow, which motivates us to propose a new PS method, called OWA-FRPS. Based on the Ordered W...