Fuzzy logic is shown to be a very promising mathematical approach for modelling traffic and transportation processes characterized by subjectivity, ambiguity, uncertainty and imprecision. The basic premises of fuzzy logic systems are presented as well as a detailed analysis of fuzzy logic systems developed to solve various traffic and transportation planning problems. Emphasis is put on the imp...

1 This work is partially supported by the FCT Portuguese Foundation for Science and Technology under project POSI/SRI/47188/2002, and by Fundação ORIENTE – Portuguese Orient Foundation ABSTRACT: Fuzzy Causal Rule Bases (FCRb) are widely used and are the most important rule bases in Rule Based Fuzzy Cognitive Maps (RB-FCM) [1][4][5][6]. However, FCRb are subject to several restrictions that crea...

It is constructively proved that the multi-input–multi-output fuzzy systems based upon genuine many-valued implications are universal approximators (they are called Boolean type fuzzy systems in this paper). The general approach to construct such fuzzy systems is given, that is, through the partition of the output region (by the given accuracy). Two examples are provided to demonstrate the way ...

Models based on neural and neuro-fuzzy structures are developed to represent knowledge about a large data set containing chemical descriptors of organic compounds, commonly used in industrial processes. The neuro-fuzzy models here proposed include both, QSARs and original numerical values. The developed approaches use various techniques to insert knowledge by training, and to map rules in neuro...

Fuzzy logic controls and neuro-fuzzy controls are accustomed to increase the performance of air conditioning system. In this paper, we are trying to provide the new design air conditioning system by exploitation two logics, namely fuzzy logic and neuro-fuzzy management. This paper proposes a set of rule and uses 2 inputs specifically temperature and humidness and 4 outputs specifically compress...

Although neuro-fuzzy models and other similar modeis have great flexibility they also have drawbacks, especially for systems which have high uncertainty associated . This paper points out which are the major drawbacks of neuro-fuzzy models and proposes a methodology to design fault detectors in uncertain systems using neuro-fuzzy models. The coolíng coil of an air-conditioning system is used as...

To accurately estimate the state of charge of a lithium-ion battery pack used in electric vehicles, a neurofuzzy system is proposed. The subtractive clustering is used to determine the structure and the initial parameters of the neuro-fuzzy system to reduce heuristic errors. The algorithm of adaptive neuro-fuzzy inference (ANFIS) is adopted to optimize the parameters of the neuro-fuzzy system. ...

Neuro{fuzzy combination are considered for several years already. However, the term \neuro{fuzzy" still lacks of proper deenition, and it has the avor of a \buzz word". In this paper we try to give it a meaning in the context of fuzzy classiication systems. From our point of view \neuro{fuzzy" means the employment of heuristic learning strategies derived from the domain of neural network theory...

An intelligent learning-based approach using neural network and fuzzy logic to the problem of interference canceling is proposed in the paper. The famous signal-processing structure of adaptive noise canceling is used for the research of interference signal canceling, in which a neuro-fuzzy system is used as the adaptive notch filter. Four T-S fuzzy rules are in the neuro-fuzzy filter. The filt...

We present an innovative adaptive, model following control scheme and apply it to control a chaotic system with unknown parameters. We illustrate the proposed approach with control of Duffing oscillator problem. The same idea is used to solve three important problems: suppression of chaos, anticontrol of chaos and chaos synchronization. We propose to use ‘approximators’ linearly parameterized b...