Global Research Performance on the Design and Applications of Type-2 Fuzzy Logic Systems: A Bibliometric Analysis

There has been a significant contribution to scientific literature in the design and applications of Type-2 fuzzy logic systems (T2FLS). The T2FLSs found applications in many aspects of our daily lives, such as engineering, pure science, medicine and social sciences. The online web of science was searched to identify the 100 most frequently cited papers published on the design and application of T2FLS from 1980 to 2016. The articles were analyzed based on authorship, source title, country of origin, institution, document type, web of science category, and year of publication. The correlation between the average citation per year (ACY) and the total citation (TC) was analyzed. It was found that there is a strong relationship between the ACY and TC (r = 0.91643, P<0.01), based on the papers consider in this research.  The “Type -2 fuzzy sets made simple” authored by Mendel and John (2002), published in IEEE Transactions on Fuzzy Systems received the highest TC as well as the ACY. The future trend in this research domain was also analyzed. The present analysis may serve as a guide for selecting qualitative literature especially to the beginners in the field of T2FLS

Dynamic evolving neural fuzzy inference system equalization scheme in mode division multiplexing for optical fiber transmission

The performance of optical mode division multiplexing (MDM) is affected by intersymbol interference (ISI) from nonlinear channel impairments arising from higherorder mode coupling and modal dispersion in multimode fiber. However, the existing MDM equalization algorithms can only mitigate the linear distortion, but they cannot address nonlinear distortion in the signal accurately. Therefore, there is a need to explore how ISI can be mitigated to recover the transmitted signal. This research aims to control the broadening of the MDM signal and minimize the undesirable distortion among channels in MMF by signal reshaping at the receiver. A dynamic evolving neural fuzzy inference system (DENFIS) equalization scheme has been used to achieve this objective. This research was conducted through a few steps commencing with modelling the MDM system in Optsim and collecting the data. Then, the signal reshaping parameters were determined. After that, DENFIS equalization, least mean square (LMS) and recursive least squares (RLS) equalizations were implemented and evaluated. Results illustrated that nonlinear DENFIS equalization scheme can improve MDM signal at a higher accuracy than previous linear equalization schemes. DENFIS equalization demonstrates better signal reshaping accuracy with an average root mean square error (RMSE) of 0.0338 and outperformed linear LMS and RLS equalization schemes with high average RMSE values of 0.101 and 0.1914 respectively. The reduced RMSE implies that DENFIS equalization scheme mitigates ISI more effectively in a nonlinear channel. This effect can hasten data transmission rates in MDM. Moreover, the successful offline implementation of DENFIS equalization in MDM encourages future online implementation of DENFIS equalization in embedded optical systems

Type-2 Takagi-Sugeno-Kang Fuzzy Logic System and Uncertainty in Machining

RÉSUMÉ: Plusieurs méthodes permettent aujourd’hui d’analyser le comportement des écoulements qui régissent le fonctionnement de systèmes rencontrés dans l’industrie (véhicules aériens, marins et terrestres, génération d’énergie, etc.). Pour les écoulements transitoires ou turbulents, les méthodes expérimentales sont utilisées conjointement avec les simulations numériques (simulation directe ou faisant appel à des modèles) afin d’extraire le plus d’information possible. Dans les deux cas, les méthodes génèrent des quantités de données importantes qui doivent ensuite être traitées et analysées. Ce projet de recherche vise à améliorer notre capacité d’analyse pour l’étude des écoulements simulés numériquement et les écoulements obtenus à l’aide de méthodes de mesure (par exemple la vélocimétrie par image de particules PIV ). L’absence, jusqu’à aujourd’hui, d’une définition objective d’une structure tourbillonnaire a conduit à l’utilisation de plusieurs méthodes eulériennes (vorticité, critère Q, Lambda-2, etc.), souvent inadaptées, pour extraire les structures cohérentes des écoulements. L’exposant de Lyapunov, calculé sur un temps fini (appelé le FTLE), s’est révélé comme une alternative lagrangienne efficace à ces méthodes classiques. Cependant, la méthodologie de calcul actuelle du FTLE exige l’évaluation numérique d’un grand nombre de trajectoires sur une grille cartésienne qui est superposée aux champs de vitesse simulés ou mesurés. Le nombre de noeuds nécessaire pour représenter un champ FTLE d’un écoulement 3D instationnaire atteint facilement plusieurs millions, ce qui nécessite des ressources informatiques importantes pour une analyse adéquate. Dans ce projet, nous visons à améliorer l’efficacité du calcul du champ FTLE en proposant une méthode alternative au calcul classique des composantes du tenseur de déformation de Cauchy-Green. Un ensemble d’équations différentielles ordinaires (EDOs) est utilisé pour calculer simultanément les trajectoires des particules et les dérivées premières et secondes du champ de déplacement, ce qui se traduit par une amélioration de la précision nodale des composantes du tenseur. Les dérivées premières sont utilisées pour le calcul de l’exposant de Lyapunov et les dérivées secondes pour l’estimation de l’erreur d’interpolation. Les matrices hessiennes du champ de déplacement (deux matrices en 2D et trois matrices en 3D) nous permettent de construire une métrique optimale multi-échelle et de générer un maillage anisotrope non structuré de façon à distribuer efficacement les noeuds et à minimiser l’erreur d’interpolation.----------ABSTRACT: Several methods can help us to analyse the behavior of flows that govern the operation of fluid flow systems encountered in the industry (aerospace, marine and terrestrial transportation, power generation, etc..). For transient or turbulent flows, experimental methods are used in conjunction with numerical simulations ( direct simulation or based on models) to extract as much information as possible. In both cases, these methods generate massive amounts of data which must then be processed and analyzed. This research project aims to improve the post-processing algorithms to facilitate the study of numerically simulated flows and those obtained using measurement techniques (e.g. particle image velocimetry PIV ). The absence, even until today, of an objective definition of a vortex has led to the use of several Eulerian methods (vorticity, the Q and the Lambda-2 criteria, etc..), often unsuitable to extract the flow characteristics. The Lyapunov exponent, calculated on a finite time (the so-called FTLE), is an effective Lagrangian alternative to these standard methods. However, the computation methodology currently used to obtain the FTLE requires numerical evaluation of a large number of fluid particle trajectories on a Cartesian grid that is superimposed on the simulated or measured velocity fields. The number of nodes required to visualize a FTLE field of an unsteady 3D flow can easily reach several millions, which requires significant computing resources for an adequate analysis. In this project, we aim to improve the computational efficiency of the FTLE field by providing an alternative to the conventional calculation of the components of the Cauchy-Green deformation tensor. A set of ordinary differential equations (ODEs) is used to calculate the particle trajectories and simultaneously the first and the second derivatives of the displacement field, resulting in a highly improved accuracy of nodal tensor components. The first derivatives are used to calculate the Lyapunov exponent and the second derivatives to estimate the interpolation error. Hessian matrices of the displacement field (two matrices in 2D and three matrices in 3D) allow us to build a multi-scale optimal metric and generate an unstructured anisotropic mesh to efficiently distribute nodes and to minimize the interpolation error. The flexibility of anisotropic meshes allows to add and align nodes near the structures of the flow and to remove those in areas of low interest. The mesh adaptation is based on the intersection of the Hessian matrices of the displacement field and not on the FTLE field