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**Skills and Expertise**

## Publications

Publications (995)

Normalized weight vector determination under bi-polar preferences is important in multi-criteria decision making and its related evaluation problems. In order to determine weights for the elements in partially ordered set which can embody bi-polar preferences, some new methods such as the ordered weighted averaging (OWA) aggregation on lattice usin...

Uncertainty in information provides the possibility of having and applying preferences, and therefore it necessitates the study of preferences involved aggregation theory and techniques under uncertainty information environments. Hence, this paper discusses several rules-based decision making methods in uncertain decision scenarios with or without...

More uncertainty can be obtained when real numbers are extended to intervals. The two new concepts proposed in this work are the natural extensions of cognitive interval information and cognitive uncertain information with real numbered values replaced by interval values. Hence, interval type cognitive interval information and interval type cogniti...

In many multi criteria group decision making problems, the individual evaluation values offered by experts are with uncertainties. Therefore, when assigning weights to those experts using preferences induced weights allocation, we can have two types of bi-polar preferences. The first one is the optimism-pessimism preference over evaluation values;...

Interval basic uncertain information is a generalization of basic uncertain information. Due to their special structures, the induced aggregation and induced OWA operators have diversified inducing aggregation modes for them. In order to provide both normative paradigms and special ways to perform reasonable induced aggregation with vectors of inte...

For the first time, this study addresses the problem of evaluating propulsion technologies for sustainable road freight distribution from the multi-criteria group decision-making perspective. It aims to help logistics companies involved in global supply chains significantly reduce greenhouse gas (GHG) emissions from freight distribution activities....

This letter reports a new type of uncertain information that is different from some well known existing uncertain information, such as probability information, fuzzy information, interval information and basic uncertain information. This type of uncertain information allows some specified compromise in interacting decision environments and gives so...

Sugeno-like operators are binary operations based generalization of Sugeno integral and are still defined on real valued fuzzy measures. This work discusses the aggregation methods in the situation where both inputs and fuzzy measures are attached with numerical uncertainties. That is, when an input vector and a fuzzy measure are given, each of the...

In social network group decision making (SN-GDM) problem, subgroup weights are mostly unknown, many approaches have been proposed to determine the subgroup weights. However, most of these methods ignore the weight manipulation behavior of subgroups. Some studies indicated that weight manipulation behavior hinders consensus efficiency. To deal with...

Complex systems are often composed of multiple subsystems arranged in a multi-level hierarchical structure. Therefore, dedicated methods suitable for determining the local states of such arranged components and the global state of the system are important. Subsystems’ dependence on each other and unreliable inputs make forming definitions of the su...

This study defines interval type basic uncertain information and BUI type basic
uncertain information, which are two extensions of basic uncertain information
and can model more types of uncertainties and uncertainty involved evaluation
problems. Under rules based and linguistic decision making environments, we
analyze and provide some classificati...

Basic uncertain information is a newly proposed normative formulation to express and model uncertain information. This study further generalizes this concept by introducing the concept of refined interval of discourse in which the true value is known to be included. Hence, we define some new definitions of relative basic uncertain information, rela...

In evaluation and decision making frequently we need to consider and then well model the subjective preferences and behaviors of decision makers. This study firstly defines literally three types of conformities, namely, the Bounded Conformity, Extreme Conformity and Bounded Extreme Conformity. Then, we define two types of value-dependent preference...

Fermatean fuzzy sets (FFSs), an orthopair fuzzy set proposed by Senapati and Yager (Journal of Ambient Intelligence and Humanized Computing 11:663–674, 2020, [24]), can handle the situation with ambiguous and incomplete information in a more effective manner than the Pythagorean fuzzy sets presented by Yager (Pythagorean fuzzy subsets, 2013 Joint I...

We introduce an analogical-problem-solving based question-answering system, LingTeQA. It generates templates from known pairs \(\langle \)question-SPARQL query \(\rangle \) and uses generated templates to answer newly asked questions. These questions can be of regular/usual form and can contain imprecise concepts represented by linguistic terms. Th...

This edited book discusses creative and recent developments of fuzzy systems and its real-life applications of multiple criteria decision-making. Keeping on the existing fuzzy sets and recent developed fuzzy sets, viz., intuitionistic fuzzy, Pythagorean fuzzy, Fermatean fuzzy, Hesitant fuzzy and multiple criteria decision approaches, this book is c...

The aggregation of fuzzy information is a new area of ‘‘intuitionistic fuzzy set (IFS)" theory that has piqued the attention of scholars in the past few years. This study aims to construct intuitionistic fuzzy (IF) aggregation operators as a result of Aczel-Alsina (AA) operations in order to shed light on decision-making issues. To begin with, some...

Basic Uncertain Information (BUI) as a newly introduced concept generalized a wide range of uncertain information. We discuss and compare some methods to derive efficacy from given BUI collection, which is helpful in decision aid. With BUI collection, we also discuss the technique of using Choquet Integral to aggregate those BUI and return closed i...

The paper develops fuzzy models to forecast cryptocurrencies prices using a data-driven fuzzy modeling procedure based on level set. Data-driven level set is a novel fuzzy modeling method that differs from linguistic and functional fuzzy modeling in how the fuzzy rules are built and processed. The level set-based model outputs the weighted average...

Decision-makers’ subjective preferences can be well modeled using preference aggregation operators and related induced weights allocation mechanisms. However, when several different types of preferences occur in some decision environment with more complex uncertainties, repeated uses of preferences induced weights allocation sometimes become unsuit...

Selecting the optimal renewable energy source (RES) is a complex multi-criteria decision-making (MCDM) problem due to the association of diverse conflicting criteria with uncertain information. The utilization of Fermatean fuzzy numbers is successfully treated with the qualitative data and uncertain information that often occur in realistic MCDM pr...

Motivated by a specific decision-making situation, this work proposes the concept and definition of unsymmetrical basic uncertain information which is a further generalization of basic uncertain information and can model uncertainties in some new decision-making situations. We show that unsymmetrical basic uncertain information in some sense can mo...

We introduce the concept of a fuzzy measure μ on a finite space X and discuss its use in providing information about the value of an uncertain variable V. Here, the measure of a subset A of X, μ(A), models the anticipation of finding the value of V in A. We are here in a situation in which the values in X are ordered and in particular, the problem...

This paper introduces the multiple linear regression heavy ordered weighted average (MLR-HOWA) operator. On the MLR-HOWA operator, the beta values are obtained with the use of the HOWA means. In that sense, it provides a new range of possibilities by under or overestimating the result based on the decision maker’s expectations and knowledge. Theref...

This paper elaborates the different methods to generate normalized weight vector in multi-criteria decision-making where the given information of both criteria and inputs are uncertain and can be expressed by basic uncertain information. Some general weight allocation paradigms are proposed in view of their convenience in expression. In multi-crite...

We introduce the concept of a fuzzy measure μ on a set X. We discuss some of the properties of a fuzzy measure. We provide some notable examples of fuzzy measures. We discuss the important application of using fuzzy measure to provide information about an uncertain variable V. Here the measure of a subset A indicates the anticipation of finding the...

As a fuzzy set (FS) expansion, the hesitant fuzzy set (HFS) is successfully employed
to demonstrate circumstances where it is admissible to ascertain a few potential membership degrees (MDs) of a component in a set because of the uncertainty between various values. Considering that there is still no research on Aczel-Alsina triangular norms and con...

There has been a renewed interest in commonsense knowledge and reasoning. To achieve artificial general intelligence, systems must exhibit not only the recognition abilities of humans but also other important aspects of being human, such as commonsense and causality. Recent literature has shown that external commonsense knowledge graphs are benefic...

Traditional association rule extraction may run into some difficulties due to ignoring the temporal aspect of the collected data. Particularly, it happens in many cases that some item sets are frequent during specific time periods, although they are not frequent in the whole data set. In this study, we make an effort to enhance conventional rule mi...

In the creation of better multiple attribute decision making (MADM) patterns to address the ambiguity in the expanding sophisticated of expert systems, the hypothesis of interval-valued intuitionistic fuzzy sets (IVIFSs) has proven to be an effective and advantageous technique. We employ Aczel-Alsina operations to remedy the MADM issue, wherein all...

A DB querying system is said to be flexible if it adapts to the end user expectations and expertise. This paper introduces a novel strategy to fuzzy querying that reduces the gap between complex search conditions end users have in mind and formal queries understood by the underlying DB system. In the Flexible Querying By Example paradigm, the propo...

This paper describes the new intuitionistic fuzzy aggregation operators in consequence of Aczel-Alsina operations that possess certain advantages in cases of solving real-life problems. We first present some new operations of intuitionistic fuzzy sets (IFSs), for example, Aczel-Alsina sum, Aczel-Alsina product, and Aczel-Alsina scalar multiplicatio...

Multi-criteria decision-making (MCDM) approaches have acquired various expansions under uncertain conditions in current years. The purpose of the current study is to broaden the implementation of the weighted aggregated sum product assessment (WASPAS) technique for decision-making (DM) in an uncertain environment. Thinking about the benefits of cub...

This study firstly proposes a simpler method for evaluating one certain object's quality with multiple criteria according to some preset evaluation threshold values that are real numbers. In real life, numerous individual valuations are provided with distributional linguistic input information and with multiple criteria, and thus they can become he...

Preferences-involved evaluation and decision making are the main research subjects in Yager’s decision theory. When the involved bipolar preferences are concerned with interval information, some induced weights allocation and aggregation methods should be reanalyzed and redesigned. This work considers the multi-criteria evaluation situation in whic...

Variance, as a measurement of dispersion, is a basic component of decision-making processes. Recent advances in intelligent systems have included the concept of variance in information fusion techniques for decision-making under uncertainty. These dispersion measures broaden the spectrum of decision makers by extending the toolset for the analysis...

The dual probabilistic linguistic (DPL) term sets are considered superior to probabilistic linguistic term sets. Further, the generalized Dombi (GD) operators are pretty flexible with the general parameters during the aggregation process. Besides, the Bonferroni mean (BM) operator has the advantage of considering interrelationships
between criteria...

Our concern here is in finding the objects in a database that have a desired value for a given attribute where our knowledge of the attribute value for the database objects is unclear. Here, the unclear attribute values are expressed using a generalized belief structure that contains both granular aspects and random aspects. Further, our target att...

The result of a multiobjective or a many-objective optimization problem is a large set of non-dominated solutions. Once the Pareto Front (or a good approximation of it) has been found, then providing the decision maker with a smaller set of “interesting solutions” is a key step. Here, the focus is on how to select such a set of solutions of interes...

OWA operators and related aggregation techniques generally focus on input vector with a linear ordering. However, in commonly faced multi-criteria and multi-sources evaluation and decision making, the inputs involved form an evaluation matrix. Considering the fact that the data under evaluation are all with two dimensional meanings, this study expl...

Volatility is an important issue for companies, policy-makers, and researches. Autoregressive conditional heteroscedasticity (ARCH) and generalized ARCH (GARCH) models are frequently used to study volatility. However, forecasting efficiency tends to fail when complex data is used. This paper proposes the use of ordered weighted average (OWA) operat...

Bi-Choquet Integrals based on bi-capacities are very powerful aggregation operators introduced by Grabisch and Labreuche, and they can generalize Choquet Integrals. Bi-capacities can model a lager range of preferences than capacities. However, there are few existent knowledge about constructing bi-capacities, and there lacks the practical and reaso...

This work proposes some standard and general forms of induced ordered weighted averaging (GnIOWA) operators where the inductive information is ordered weighted averaging (OWA) weight vectors instead of real numbers. It shows the usefulness of such type of generalized induced OWA in decision making and evaluation and many other applications. We prop...

Basic Uncertain Information (BUI) as a newly introduced concept generalized a wide range of uncertain information. The well-known Ordered Weighted Averaging (OWA) operators can flexibly and effectively model bipolar preferences of decision makers over given real valued input vector. However, there are no extant methods for OWA operators to be carri...

Most of the evaluation problems are comprehensive and with ever-increasingly more uncertainties. By quantifying the involved uncertainties, Basic Uncertain Information can both well handle and merge those uncertainties in the input information. This study proposed a two-level comprehensive evaluation model by using some merging techniques which can...

The ordered weighted averaging (OWA) operator and its associated weight vectors have been both theoretically and practically verified to be powerful and effective in modeling the optimism/pessimism preference of decision makers. When several different OWA weight vectors are offered, it is necessary to develop certain techniques to aggregate them in...

With some theoretical derivation and practical decision making problem, this study proposes a constructing paradigm for generating fuzzy measures in some certain decision situations, such as in risk evaluation and decision making. The constructing paradigm involves four constructing factors: source measure space, construction function, construction...

Discrete Ordered Weighted Averaging (OWA) operators as one of the most representative proposals of Yager (1988) have been widely used and studied in both theoretical and application areas. However, there are no effective and systematic corresponding methods for continuous input functions. In this study, using the language of measure (capacity) spac...

The evaluation for online shopping platform is the basis for further decision and policy taking. The collected individual opinion and evaluation information are often represented by some linguistic/preference vectors. Further aggregating those vector needs to simultaneously consider two contradictory factors: the original weights assigned and the i...

The evaluation and decision taking methods proposed in this study bypass some final result obtained by performing traditional aggregation operators, and thus they provide some alternative way and choice for decision making and add diversity and flexibility as well. To achieve this purpose, three different types of partitions of input space are intr...

In this study, some examples show that Hirsch's index (h-index) usually has some limitation in evaluations. In order to provide more choices and diversities for scientometrics evaluation index, this study discusses four types of extended indexes. We firstly use a type of variation of Cognitive Integral to serve as a new generalized Hirsch's index,...

This study proposes some extended aggregation operators to model Extreme Conformity and Bounded Extreme Conformity which were proposed in a recent work. In detail, we propose Interval Judged s-t-A extreme operators and Selective Leveled-Preferences Ordered Weighted Averaging operators, respectively, and analyze some of their properties such as the...

Imprecise and subjective concepts, as e.g. promising students, may be used within data mining tasks or database queries to faithfully describe data properties of interest. However, defining these concepts is a demanding task for the end-user. We thus provide a strategy, called CHOCOLATE, that only requires the user to give a tiny subset of data poi...

Knowledge graphs are a data format that enables the representation of semantics. Most of the available graphs focus on the representation of facts, their features, and relations between them. However, from the point of view of possible applications of semantically rich data formats in intelligent, real-world scenarios, there is a need for knowledge...

This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtual...

This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtual...

This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtual...

The Crescent Method is a recently proposed decision method that can consider problems involving both risk and preferences. In this work, we elaborately discuss why and how to use this interesting method in decision making. We present its advantages in accurately merging both types of decisions. However, not all preferences are suitable to use with...

In human processed AI, HP-AI, we build our AI systems based on knowledge learned by human experts rather then that learned by artificial neural networks such as in the case of deep learning. The information provided by these human experts is typically linguistically expressed. In support of HP-AI we look at the properties of an ordinal scale, S, ne...

OWA operators have been used in a lot of applications showing the great interest and applicability of these versatile operators. This paper introduces an extension of OWA operators allowing a greater level of flexibility. The new meta notion of OWA operator provides the use of different kind of OWA operators to the same dataset. Different interesti...

A monotonicity of Interval Sugeno Integrals proposed in “X. Pu, R. Mesiar, R.R. Yager, L. Jin, Interval Sugeno Integral With Preference, IEEE Trans. Fuzzy Syst. 28 (2020) 597—601.” has been found not correct with a counter example. This letter presents this counter example and analyzes the reason behind that cause such non-monotonicity. In addition...

This work firstly proposes some weight adjusting and preference interfering methods to generate more suitable weight vector in two-tier multi-criteria decision making. The proposed models simultaneously consider the original weight information and subjective preferences of decision makers under interval numbers based evaluation environments. A rece...

Discovering interesting and useful association rules from the collected data is an issue of great importance in pattern mining. Although a myriad of association rules can be extracted with traditional rule mining techniques, some of the obtained rules might be redundant or even meaningless in many cases. To overcome this difficulty, logical formula...

Our concern is with selecting the best alternative in the face of uncertain satisfactions by the alternatives. Here, we use a measure to model the uncertain outcomes. We look at various approaches for formulating the concept of best in this case of uncertain outcomes. We consider the case where we have one criterion of interest as well as the case...

Induced OWA operators are important extensions of OWA operators and can suit more different decision environments. However, when practitioners perform Induced OWA operators, they frequently do not considered the tied values in inducing information, therein lay the problem of possible non-uniqueness of aggregation results. From a novel perspective t...

We first describe an approach to multi-criteria making which makes use of a fuzzy measure over the set of criteria to model the user expressed relationship between the criteria. Under this approach we use the Choquet integral, guided by this fuzzy measure, to aggregate an alternative’s satisfactions to the individual criteria. Our focus in this pap...

Dynamical models of autonomous systems usually follow general assumption about rationality of the systems and their judgements. In particular, the systems acting under uncertainty are defined using probabilistic methods with the reasoning based on minimization or maximization of the expected payoffs or rewards. However, in the systems that deal wit...

In this paper, we propose Fermatean fuzzy sets. We compare Fermatean fuzzy sets with Pythagorean fuzzy sets and intuitionistic fuzzy sets. We focus on complement operator of Fermatean fuzzy sets. We find out the fundamental set of operations for the Fermatean fuzzy sets. We define score function and accuracy function for ranking of Fermatean fuzzy...

The well-known Choquet Integrals are based on given fuzzy measures, providing some sound schemes for the evaluation problems in multi-criteria decision making. To further generalize and diversify these interesting aggregation functions, this study proposes the concept of derived fuzzy measures, which can serve as a generalization of normally used f...

Yager's q-rung orthopair fuzzy set (q-ROFS) is a generalization of fuzzy sets, whose prominent feature is that the q-th power sum of the membership and the non-membership degrees is equal to or less than one, and we call its core, an ordered pair, q-rung orthopair fuzzy number (q-ROFN). More recently, the scholars have constructed the q-rung orthop...

This study first revamps Yager prioritized ordered weighted averaging operators, and condenses them into a conceptual frame with putting aside one realization from Yager's original proposal. Then, based on elicited conceptual frame called Yager prioritized preference conceptual frame, this article proposes three distinct realizations to the concept...

Induced ordered weighted averaging is a powerful tool in decision making, and different inducing variables generally determine different types of IOWA. The existing studies and applications of IOWA often is non-systematical and decision makers may often be confused with several problems such as how to effectively and fast determine and obtain induc...

Although plenty of techniques such as link prediction, clustering, and position analysis have been proposed to analyze social and economic networks and patterns of social and economic relationships in various fields, few studies have addressed the transformation of social and economic network data into the knowledge in the form of linguistic summar...

Fuzzy Cognitive Maps (FCMs) play an important role in high level reasoning, but are limited in their ability to model complex systems with singularities. We are interested in systems which exhibit discontinuous behaviors as one or more of their internal node states approaches a threshold. In a new approach to FCM dynamics, we define general classes...

A moving average is an average that aggregates a subset of variables from the set and moves across the sample. It is widely used in time-series forecasting. This paper studies the use of moving averages in some representative aggregation operators. The ordered weighted averaging weighted moving averaging (OWAWMA) operator is introduced. It is a new...

The philosophy of soft sets is founded on the fundamental idea of parameterization, while Pawlak's rough sets put more emphasis on the importance of granulation. As a multivalued extension of soft sets, the newly emerging concept called N-soft sets can provide a finer granular structure with higher distinguishable power. This study offers a fresh i...

Fermatean fuzzy sets (FFSs), proposed by Senapati and Yager (0000), can handle uncertain information more easily in the process of decision making. They defined basic operations over the Fermatean fuzzy sets. Here we shall introduce four new weighted aggregated operators, namely, Fermatean fuzzy weighted average (FFWA) operator, Fermatean fuzzy wei...

Multiple‐criteria decision problems involve selecting an alternative that best satisfies a collection of criteria as quantified by a scalar corresponding to an aggregation of the alternatives satisfaction to the individual criteria. A fundamental issue is the formulation of decision maker's aggregation function based upon the decision maker's perce...

This work discusses some new types of bipolar preferences and defines conservativeness of them. Then, the study defines parameterized fuzzy measures and proposes three methods to generate them. Based on given conservativeness preference and some special evaluation functions, we majorly discuss preference leveled evaluation functions method to const...

This study proposes a novel concept of Scatter for probability distribution (on [0,1]). The proposed measurement is different from famous Shannon Entropy since it considers [0,1] as a chain instead of a normal set. The measurement works easily and reasonably in practice and conforms to human intuition. Some interesting properties like symmetricity,...

Existing extensions to Yager's ordered weighted averaging (OWA) operators enlarge the application range and to encompass more principles and properties related to OWA aggregation. However, these extensions do not provide a strict and convenient way to model evaluation scenarios with complex or grouped preferences. Based on earlier studies and recen...