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Multi objective linguistic optimization is a useful mathematical technique to solve problems that interdependent criteria. In such problems, values of the objective functions may be unknown at some points, when the link between the variables and the objective functions are defined linguistically through if-then rules. While solving this type of problems, Tsukamoto based reasoning method has proved...
Fuzzy Systems are an efficient instrument to create efficient and transparent models of the behavior of complex dynamic systems such as autonomous humanoid robots. The human interpretability of these models is particularly significant when it is applied to the cognitive robotics research, in which the models are designed to study the behaviors and produce a better understanding of the underlying processes...
The study of human remains suffers from a lack of information for determining a reliable estimation of the age of an individual. One of the most extended methods for this task was proposed in the twenties of the past century and is based on the analysis of the pubic bone. The method describes some age changes occurring in the pubic bone and establishes ten different age ranges with a description of...
In the medical field determination of appropriate rate of insulin injection in order to stabilize the blood glucose to a normal level is vital for diabetics. In this paper, an adaptive neuro-fuzzy inference system (ANFIS) based on hybrid blood glucose control data set has been presented. Hybrid blood glucose control employs combination of the fuzzy logic controller optimized by genetic algorithm with...
In this paper, a comparison of the behaviour of fuzzy decision trees and gradual fuzzy decision trees is presented in a real-world application in the context of labour economics. The aim of this study is on one hand to present, in a real case, the good property of interpretability of such decision trees. On the other hand, it shows the importance to take into account a graduality relation between...
Question answering (QA) is a challenging task and has received considerable attention in the last years. Answer selection among candidate answers is one of the main phases for QA and the best answer to be returned is determined in this phase. A common approach consists in considering the selection of the final answer(s) as a ranking problem. So far, different methods have been proposed, mainly oriented...
Various evolutionary multiobjective optimization (EMO) algorithms have been used in the field of evolutionary fuzzy systems (EFS), because EMO algorithms can easily handle multiple objective functions such as the accuracy maximization and complexity minimization for fuzzy system design. Most EMO algorithms used in EFS are Pareto dominance-based algorithms such as NSGA-II, SPEA2, and PAES. There are...
This paper considers a regulation problem of non-linear large-scale systems. To do this, a Takagi-Sugeno (T-S) fuzzy model is adopted for fuzzy modeling of the nonlinear large-scale systems, which has unknown interconnection terms. An output-feedback decentralized fuzzy controller with integral action is employed to drive the system outputs to reach a reference value and minimize the steady-state...
This paper proposes a new approach for single frame image super resolution using multiple ANFIS (Adaptive Network-based Fuzzy Inference System) mappings. It presents an implemented learning system that captures the relationship between a low resolution (LR) image patch space and a high resolution (HR) one given an external image database. In particular, a collected large number of LR and HR image...
This paper develops conditions for sensor fault detection and isolation of nonlinear descriptor systems. The proposed methodology is based on a bank of observers, thus a novel approach is proposed to design Takagi-Sugeno observers in descriptor form. Traditionally, for descriptor systems, the designing conditions employ an augmented state vector whose elements are the state and its derivative. The...
The classical fuzzy discriminant analysis with kernel methods (KFDA) is an effective method of solving nonlinearity pattern analysis problem. In some complicated cases, the kernel machine constituted by a single kernel function is not able to meet some practical application requirements, such as heterogeneous information or unnormalised data, non-flat distribution of samples, etc. By searching for...
In this paper we apply the Fuzzy Entropy and Approximate Entropy measures to the Activities of Daily Living (ADL) for a set of elderly subjects in their own homes, and compare the entropy measures against a simpler count of activity transitions. The aim is to assess whether a single relatively simple measure can give an overview of the ADL in order to provide summaries of the wellbeing of an elderly...
In the last years, the growing adoption of cloud-based multi-tiers systems has strongly increased the levels of resource sharing among companies, improving the enterprise efficiency, thanks to a refined business dynamism and a rapid decrease in costs. However, in spite of their advantages, this new business model highlights the emergence of new computational approaches aimed at the distribution and...
Denial of service flood attacks are among the most common and powerful attacks which abuse the computational resources and the bandwidth of a network. In this paper, a heterogeneous defense method is proposed based on a combination of the Software Defined controller and fuzzy decision making. Numerical results show that the proposed method has a lower computational load and response time compared...
We further develop our concept of a compound query (cf. Kacprzyk and Zadroižny [23]) in which in a bipolar query comprising of a required and desired condition aggregated via a non-conventional operator corresponding to “and if possible” the particular required and desired conditions are by themselves queries with fuzzy linguistic quantifiers. We use our approach to the dealing with data quality (trustworthiness),...
We define expanded hesitant fuzzy sets, which incorporate all available information of the decision makers that provide the membership degrees that define a hesitant fuzzy set. We show how this notion relates to hesitant fuzzy set and extended hesitant fuzzy set. We define various scores for this setting, which generalize popular scores for hesitant fuzzy elements. Finally, a group decision making...
Generation of linguistic summaries that are compact, short and relevant to the user remains an open challenge. In this paper, we propose a novel method for improving the generation of linguistic summaries inspired by the a-priori algorithm and the degree of appropriateness. The method generates all true summaries with related predicates in the summarizer, resulting in a small set of linguistic summaries,...
Fuzzy Markup Language (FML) presented by IEEE Computational Intelligence Society (CIS) has been an IEEE Standard since May 2016. It is an XML-based language for designer to easily construct the knowledge base and rule base of the developed fuzzy logic system. In this paper, we propose an FML-based linguistic classification agent and apply it to popular Chinese songs' classification in social media...
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