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The paper considers basic phases of fuzzy systems construction: expert evaluation, structure identification, parameter estimation. For solving the problem optimization of fuzzy systems parameters applied the Great Deluge algorithm. Experiments for analyzing the performance of the algorithms for optimization and fuzzy system are described.
Robots are being used more and more in dangerous environments such as space and disaster areas. However, when robots are at risk in dangerous environments, the time during which robot operators can issue risk avoidance instructions is limited. Therefore, robots should be able to acquire behaviors that enable them to autonomously avoid danger. In this paper, we present a probability-based reinforcement...
In this paper, we develop a novel multi-fusion brain-computer interface (BCI) based on linear discriminant analysis (LDA) to deal with motor imagery (MI) classification problem. We combine filter bank and sub-band common spatial pattern (SBCSP) to extract features from EEG data in the preprocessing phase, and then LDA classifiers are applied to classify brain activities to identify either left or...
In this paper, the problem of reducing the risks involved in the critical situations in the techno-social systems with complicated infrastructure and characterized by large crowds, such as airports, train stations, shopping centers, etc. is considered. The task is to be solved with technical safety system on the basis of fuzzy decision support system and self-organizing sensor system. Architectures...
The aim of this note is to introduce the notion of fuzzy congruence relation on pseudo BE-algebras and investigate their properties. We show that the set of fuzzy congruence relations of a pseudo BE-algebra is a complete lattice. Moreover, the quotient structure induced by fuzzy congruence relations are studied.
In this paper, inspired by the concept of intuitionistic fuzzy lattices previously introduced by Thomas and Nair, we introduce the notion of intuitionistic fuzzy complete lattice and investigate some of its basic properties. In particular, some interesting characterizations closely related to the intuitionistic fuzzy complete lattices are given.
In this paper, we propose a method of nursing-care text classification. We have proposed some nursing-care classification methods using fuzzy systems, standard three-layer neural networks, and support vector machines. Also we have proposed several types of feature vector definitions for expressing free style Japanese texts into numerical vectors. This paper proposes a novel feature vector definition...
Given a finite totally ordered set of linguistic descriptions, the extended set of qualitative labels with different levels of precision L is constructed. In this framework, qualitative descriptions of a given set are L-fuzzy sets. A distance between L-fuzzy sets is introduced based on the properties of the lattice L. An illustrative example in the retail sector applied to assess a firm's overall...
As robot technology grows, more attention is being paid to educational-support robots that assist in learning. For example, an educational-support robot may support students in their school life or help them learn other languages. However, users tend to lose interest in educational-support robots. To solve this problem, a model of emotional expressions has been proposed in human-agent interaction...
Build classifier based on fuzzy rules for high-dimensional data sets, such as genetic data, are faced with great difficulties. An effective approach to this problem using feature selection techniques and dimension reduction methods. Hence, in this paper, using five different feature selection methods, size of data is reduced and the based on accuracy of the support vector machines classifier to this...
In this work, we discuss how the Lewinian model of experiential learning theory can be modeled in the framework of fuzzy logic. Fuzzy inference mechanism has been used to model the Lewinian model. Each stage of the Lewinian model has been modeled by appropriate step of a fuzzy inference mechanism.
In this study, we are aimed to the Route Search which satisfied the preferences of individual drivers. Preferences here are those primarily involved in the Route Search, for example there are various elements of preference, such as a route of a few traffic accidents. The preference is fuzzy due to human subjectivity and feeling. When considering the multiple elements of preference, it is difficult...
This papers proposes two novel approaches for the identification of Takagi-Sugeno fuzzy models with time variant and invariant features. The proposed Mixed Fuzzy Clustering algorithm is proposed for determining the parameters of Takagi-Sugeno fuzzy models in two different ways: (1) the antecedent fuzzy sets are determined based on the partition matrix generated by the Mixed Fuzzy Clustering algorithm;...
Regression Analysis is an analyzing method of regression model to explain the statistical relationship between explanatory variables and response variables. This paper propose a new regression analysis applying Theil's method based on F-transform. The main advantage of Theil's method in regression is the robustness, which means that it is not sensitive to outliers. The proposed method uses the median...
Hesitant fuzzy sets are an extension of ordinary fuzzy sets. They are composed of dual hesitant fuzzy sets, interval valued hesitant fuzzy sets, generalized hesitant fuzzy sets, hesitant fuzzy linguistic term sets, and triangular fuzzy hesitant fuzzy sets. Multi-experts evaluations are integrated by aggregation operators. This paper develops the fuzzy annual cash flow analysis using triangular hesitant...
A fuzzy route planning model based on preference degrees of stops is proposed in this study. The proposed model might also be evaluated as an intelligent system that simulates human behavior in selecting a stop to use in transportation aim. Definitions of fuzzy stop-stop, stop-line and line-line neighborhood relations are introduced. Some criteria such as the walking distance, the count of boarding...
In this paper we want to stress the relevance of paired fuzzy sets, as already proposed in previous works of the authors, as a family of fuzzy sets that offers a unifying view for different models based upon the opposition of two fuzzy sets, simply allowing the existence of different types of neutrality associated to the different semantic relationships that may hold between opposite references. This...
The rationale behind ensemble machine learning systems is the creation of many classifiers and the combination of their output such that the combination improves the performance of each single classifier. There are two key issues in the creation of ensemble classifiers: one is how two select and group the data samples to train the individual models and the other is how to select or combine the multiple...
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