This work introduces an innovative approach from modeling to simulations, integrating quantum fuzzy interpretations, focusing on the expression of membership degrees in quantum circuits, interpreted as a unitary quantum transformation. Our research contrasts Quantum Fuzzy Computing with Classical Computing, particularly in the context of the prisoner's dilemma and parent-child relationships. Through the Qiskit framework, we conduct simulations, demonstrating the differences in results obtained by both approaches. Well-known fuzzy connectives, such as “exclusive or” and “arithmetic means”, provide an algebraic description for the corresponding composition of quantum operators and circuit representations. Thus, such algorithms can easily extend to model multiple agents' relationships, described by multidimensional quantum registers. The Qiskit simulations provide the structure for the algorithms' computation on the actual quantum platforms, indicating a promising direction for future research in this hybrid research area.

In this paper, we discussconsensus measures for typical hesitant fuzzy elements (THFE), which are the finite and nonempty fuzzy membership degrees under the scope of typical hesitant fuzzy sets (THFS). In our approach, we present a model that formally constructs consensus measures by means of aggregations functions, fuzzy implication-like functions and fuzzy negations, using admissible orders to compare the THFE, and also providing an analysis of consistency on them. Our theoretical results are applied into a problem of decision making with multicriteria illustrating our methodology to achieve consensus in a group of experts working with THFS.

Multi Expert-Multi Criteria Decision Making (ME-MCDM) problems have been well explored on hesitant fuzzy environments dealing with membership degrees as subsets which do not necessarily have the same cardinality. Admissible (total) orders collaborate by reducing the collapse in the ranking of alternatives related to preference relations. In such context, three classes of admissible orders are presented in a non-restrictive way, integrating the concepts of linearity and cardinality and providing support to the comparison between two typical hesitant fuzzy elements. In the sense of hesitant fuzzy logic, the study of fuzzy operators and their main properties is extended considering the admissible linear orders. Namely, the typical hesitant fuzzy aggregation functions, negations and implication functions are discussed mainly related to their (iso/anti)tonicity properties w.r.t. these admissible orders. An algorithmic procedure is introduced illustrating our strategy to solve an ME-MCDM problem, by selecting a Computer Integrating Manufacturing software and making use of the achieved theoretical results.

Currently, billions of resources are connected to the Internet, many providing services. There is forecast to be a significant increase in the number of resources in the coming years. The adequate selection of resources that best meet the demands of users among a large number of options has been a relevant and current research challenge in the autonomic IoT management. This paper specifies and evaluates the pre-classification of new resources of the EXEHDA middleware based on the non-functional parameters of QoS. Fuzzy logic is used in the treatment of uncertainties in defining the importance weights of QoS attributes. The results obtained in the evaluation of the accuracy of the pre-classification through fuzzy logic and machine learning are presented.

This paper aims to study the robustness of f-Xor connectives, in particular the ETP, SP, NSoperator also including its main properties, NS-dual construction and corresponding fuzzy f-Xor implication and bi-implication. Additionally, we obtained some basic results on the pointwise sensitivity of the f-Xor connective ETP, SP, NS, mainly connected with the endpoints of unit interval U. Our major interest is the robustness analysis related to f-X(N)or (co)implications and f-X(N)or bi-(co)implications.

Since the seminal paper of fuzzy set theory by Zadeh in 1965, many extensions have been proposed to overcome the difficulty for assigning the membership degrees. In recent years, a new extension, the hesitant fuzzy sets, has attracted a lot of interest due to its usefulness to handle those problems in which it is difficult to provide accurately a single membership value; since for hesitant sets, membership values are given by a whole set of values. On the other hand, since fuzzy negations have an important role in applications as well as in the theoretical approach to of fuzzy logics, it is important to study an extension of the concept of fuzzy negation for hesitant fuzzy degrees (elements). In this paper, we propose such a definition and we study some of the main properties of this new concept.

The simulation of quantum algorithms in classic computers is a task which requires high processing and storing capabilities, limiting the size of quantum systems supported by the simulators. However, optimizations for reduction of temporal and spatial complexities are promising, expanding the capabilities of some simulators. The main contribution of this work consists in designing optimizations resulting from the description of quantum transformations using Quantum Processes and Partial Quantum Processes conceived in the qGM theoretical model. These processes, when computed on the VPE-qGM execution environment, require low execution time and result in the improvement of the performance, allowing the simulation of more complex quantum algorithms. The performance evaluation of this proposal was performed by benchmarks used in similar works and included the sequential simulation of quantum algorithms up to 24 qubits. The results are promising when compared to the state-of-art, indicating the possibilities of advances in this research.

The paper presents a general expression of an interval-valued intuitionistic fuzzy coimplication generated by interval-valued aggregation function acting on a pair of mutual dual functions, named interval-valued fuzzy implications and coimplications. We analyse under which conditions such connectives preserve the main properties of intuitionistic fuzzy implications. In addition, interpretations of conditional fuzzy rules based on interval-valued fuzzy logic and intuitionistic fuzzy logic are considered.