In this paper, passivity analysis of fractional-order neutral-type fuzzy cellular bidirectional associative memory (BAM) neural networks with time-varying delays is investigated. Based on the Lyapunov–Krasovskii functional, delay-dependent sufficient conditions for solvability passive problem are obtained in terms linear matrix inequalities (LMIs), which can be easily checked by using MATLAB LM...

short-term prediction of traffic flow is central to alleviating congestion and controlling the negative impacts of environmental pollution resulting from vehicle emissions on both inter- and intra-urban highways. the strong need to monitor and control congestion time and costs for metropolis in developing countries has therefore motivated the current study. this paper establishes the applicatio...

improving time series forecastingaccuracy is an important yet often difficult task.both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. in this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...

This paper proposes a fuzzy inference based neural network for the forecasting of short term loads. The forecasting model is the integration of fuzzy inference engine and the neural network, known as Fuzzy Inference Neural Network (FINN). A FINN initially creates a rule base from existing historical load data. The parameters of the rule base are then tuned through a training process, so that th...

We describe in this paper the use of neural networks and type-2 fuzzy logic for pattern recognition. In particular, we consider the case of speaker recognition by analyzing the sound signals with the help of intelligent techniques, such as the neural networks and fuzzy systems. We use the neural networks for analyzing the sound signal of an unknown speaker, and after this first step, a set of t...

This paper presents an efficient fuzzy neural system which consists of modular neural networks combined by the fuzzy integral with ordered weighted averaging (OWA) operators. The ability of the fuzzy integral to combine the results of multiple sources of information has been established in seL'eral preL'ious works. The key point of this paper is to formalize modular neural networks as informati...

We describe in this paper the use of neural networks, fuzzy logic and genetic algorithms for voice recognition. In particular, we consider the case of speaker recognition by analyzing the sound signals with the help of intelligent techniques, such as the neural networks and fuzzy systems. We use the neural networks for analyzing the sound signal of an unknown speaker, and after this first step,...

Nowadays fuzzy neural networks have been successfully applied to intelligent diagnosis of many diseases. This paper applies union-based fuzzy neural networks to intelligent diagnosis of hepatitis disease that is very common in the world and needs to be diagnosed exactly. Union-based fuzzy neural networks can guarantee a reduced knowledge base with subset of all possible rules by allowing union ...