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The papers in this special section provide a series of high quality papers which significantly contribute to new theories, applications, and algorithms about uncertain multicriteria decision making. It not only reports recent significant developments but also highlights potential, growing research directions, and future trends, which will benefit researchers in studying theories, applications, and algorithms about uncertain multicriteria/ multiobjective/multiattribute decision making. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM AUTHOR]

Provides instructions and guidelines to prospective authors who wish to submit manuscripts. [ABSTRACT FROM AUTHOR]

The usage of the standard h-index to compare scientists from different research fields is often misleading. To avoid this possible failure, based on the Sugeno integrals, three new modified indices Hα, Hβ , and Hαβ are proposed, thus, allowing to compensate the lower number of citations or of papers characteristic for a considered field. Our approach has a transparent geometric interpretation, and thus, it offers good candidates to replace the standard h-index H in considered databases, such as Web of Science (WOS), Scopus, or Google Scholar. [ABSTRACT FROM AUTHOR]

Provides instructions and guidelines to prospective authors who wish to submit manuscripts. [ABSTRACT FROM AUTHOR]

Evolving fuzzy systems (EFSs) are now well developed and widely used, thanks to their ability to self-adapt both their structures and parameters online. Since the concept was first introduced two decades ago, many different types of EFSs have been successfully implemented. However, there are only very few works considering the stability of the EFSs, and these studies were limited to certain types of membership functions with specifically predefined parameters, which largely increases the complexity of the learning process. At the same time, stability analysis is of paramount importance for control applications and provides the theoretical guarantees for the convergence of the learning algorithms. In this paper, we introduce the stability proof of a class of EFSs based on data clouds, which are grounded at the AnYa type fuzzy systems and the recently introduced empirical data analytics (EDA) methodological framework. By employing data clouds, the class of EFSs of AnYa type considered in this paper avoids the traditional way of defining membership functions for each input variable in an explicit manner and its learning process is entirely data driven. The stability of the considered EFS of AnYa type is proven through the Lyapunov theory, and the proof of stability shows that the average identification error converges to a small neighborhood of zero. Although, the stability proof presented in this paper is specially elaborated for the considered EFS, it is also applicable to general EFSs. The proposed method is illustrated with Box–Jenkins gas furnace problem, one nonlinear system identification problem, Mackey–Glass time series prediction problem, eight real-world benchmark regression problems as well as a high-frequency trading prediction problem. Compared with other EFSs, the numerical examples show that the considered EFS in this paper provides guaranteed stability as well as a better approximation accuracy. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM PUBLISHER]

The famous Hirsch index has been introduced just ca. ten years ago. Despite that, it is already widely used in many decision-making tasks, like in evaluation of individual scientists, research grant allocation, or even production planning. It is known that the $h$-index is related to the discrete Sugeno integral and the Ky Fan metric introduced in the 1940s. The aim of this paper is to propose a few modifications of this index as well as other fuzzy integrals—also on bounded chains—that lead to better discrimination of some types of data that are to be aggregated. All of the suggested compensation methods try to retain the simplicity of the original measure. [ABSTRACT FROM PUBLISHER]

This paper presents a time-series classification method based on fuzzy cognitive maps. We advocate that fuzzy cognitive maps provide a sound representation of time series, and we can construct a classification mechanism based on them. The classifier has to distinguish maps constructed for time series belonging to different classes. The proposed classification procedure evaluates similarity of fuzzy cognitive maps, and it is done by comparing weight matrices based on the same set of concepts. A weight matrix describes relationships between concepts in a map. Concepts represent the underlying data, because they are extracted via a data-driven clustering procedure. Each data point of a time series is related to each concept, and we evaluate the strength of relationships with a membership function. This paper investigates performance of the proposed approach on a suite of real-world datasets. We compare classification accuracy of our method with 37 state-of-the-art time-series classification methods. Experiments show that the proposed method is performing well. In many cases, it is better than its competitors. [ABSTRACT FROM AUTHOR]

This paper focuses on the sliding mode control (SMC) problem of interval type-2 (IT2) fuzzy systems subject to the unmeasurable state and cyberattacks. A key issue is how to design a state observer under the constraint that only the bounds of membership functions are known. To this end, this paper introduces two weighting factors to construct a new membership function. Besides, the concept of input-to-state stability (ISS) is utilized to deal with the residual term resulting from the cyberattacks and external disturbances. The sufficient condition is established such that the sliding mode dynamics and the estimated error dynamics are input-to-state stable. Furthermore, by online estimating the unknown parameters in upper bounds of cyberattacks and external disturbances, an adaptive sliding mode controller is synthesized such that the reachability of the prescribed sliding surface can be guaranteed and the effect of cyberattacks on the system performance can be effectively attenuated. Finally, the validity of the proposed method is illustrated by a mass–spring–damper system. [ABSTRACT FROM AUTHOR]

Presents the statement of editorial policy for this issue of the publication. [ABSTRACT FROM AUTHOR]

These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal. [ABSTRACT FROM PUBLISHER]

Till now, there are lots of stability and stabilization results about Takagi–Sugeno (T–S) fuzzy systems with time delay, but most of them are independent of the analysis of membership functions. Since the membership functions are an essential component to make a fuzzy system different from others, the conditions without its information are conservative. In this brief paper, a new Lyapunov–Krasovskii functional is designed to investigate the stability and stabilization of continuous-time T–S fuzzy systems with time delay. Different from the existing results in the literature, the integrand of the Lyapunov–Krasovskii functional in this paper depends not only on the integral variable, but also on the membership functions, and thus, the information of the time derivative of membership functions can also be used to reduce the conservativeness of finding the maximum delay bounds. Utilizing the information of the time derivative of membership, a number of controllers are designed according to their sign, and then, a switching idea is applied to stabilize the fuzzy system. In the end, two examples are given to illustrate the feasibility and validity of the design and analysis. [ABSTRACT FROM AUTHOR]

In this paper, relaxed observer-based state estimation of discrete-time Takagi–Sugeno fuzzy systems is proposed via developing a new augmented matrix approach. In contrast with the recent method reported in the literature, a more advanced introduction mode of additional matrices is developed without any redundant constraint under the framework of homogeneous polynomials. Then, the proposed augmented matrices can be built in order to depict the characteristic information of each possible working mode in a superior way, and thus our obtained result is less conservative than the recent one. Moreover, it is worth noting that that the recent method belongs to the special case of ours. Finally, two numerical simulations are given to test and validate the superiority and generality of the developed method. [ABSTRACT FROM AUTHOR]

Provides instructions and guidelines to prospective authors who wish to submit manuscripts. [ABSTRACT FROM AUTHOR]

Over the last few decades, pattern classification has become one of the most important fields of artificial intelligence because it constitutes an essential component in many different real-world applications. Artificial neural networks and fuzzy logic are two most widely used models in pattern classification. To build an efficient and powerful model, researchers have introduced hybrid models that combine both fuzzy logic and artificial neural networks. Among the hybrid models, the fuzzy min–max (FMM) neural network has been proven to be a premier model for undertaking pattern classification problems. While FMM is useful in terms of its capability of online learning, it suffers from several limitations in the learning procedure. Therefore, over the past years, researchers have proposed numerous improvements to overcome the limitations of the original FMM model. This paper carries out a comprehensive survey of the developments conducted on the FMM model for pattern classification. In order to assist recent researchers in selecting the most suitable FMM variant and to provide proper guidance for future developments, this study divides the variants of FMM into two main board categories, namely FMM variants with and without contraction. This division facilitates understanding of the developments conducted by researchers on the original FMM neural network, as well as provides the scope to identify the limitations that still exist in the FMM models. This paper also summarizes the use of FMM and its variants in solving different benchmark and real-world problems. Finally, the possible future trends are highlighted. [ABSTRACT FROM AUTHOR]

This paper deals with the concept and application of general three-dimensional (3-D) type-2 fuzzy logic systems in the polar frame (G3DT2FLS). 1 Because many acronyms are used in this paper, they are summarized in for the convenience of the reader. We focused on the automatic membership function (MF) Generator, general type-2 polar fuzzy membership, new geometric operators in polar frame, inference consisting of fuzzy 3-D polar rules and antecedents/consequents $\theta$ -slice and $\alpha$ -planes. The cubic smoothing spline is introduced to generate the upper and lower MFs according to the information theory. Three indices of compactness, smoothness, and entropy are employed for tuning of MFs. A measure of ultrafuzziness, min, max, equal, and reduced ultrafuzziness are suggested for the polar method. Additionally, the set theoretic operations of 3-D type-2 fuzzy sets in the polar frame are discussed. We also prove the join, meet, centroid, and type-reduction operations in the polar frame. Several rule sets are given to show the usefulness and complexity of the proposed method. The performance of the partial general 3D polar type-2 fuzzy logic system showed linear growth as the number of rules was increased. Computation time tests showed that the algorithm reduces the computation time by a maximum of 67% compared with discrete MF and is shown by an extreme 98% for the geometric procedure. These results indicate significant improvements in computation time for the spline interpolation over the existing methods. [ABSTRACT FROM AUTHOR]