We consider a generalized model of neural network with a fuzziness and chaos. The origin of the fuzzy signals lies in complex biochemical and electrical processes of the synapse and dendrite membrane excitation and the inhibition mechanism. The mathematical operations included into fuzzy neural network modeling are: the scalar product between inputs of layers and synaptic weights is replaced by...

A method for response integration in modular neural networks with type-2 fuzzy logic for biometric systems p. 5 Evolving type-2 fuzzy logic controllers for autonomous mobile robots p. 16 Adaptive type-2 fuzzy logic for intelligent home environment p. 26 Interval type-1 non-singleton type-2 TSK fuzzy logic systems using the hybrid training method RLS-BP p. 36 An efficient computational method to...

Fuzzy neural network combines the theories of fuzzy logical and neural network, including learning, association, identification, self-adaptation and fuzzy information process. The logic neurons have received much concern all the time as the important components of neural networks. From the models designing to the algorithms studying, there are many achievements. Glorennec[1]proposed a general a...

A work on neural network and fuzzy logic based technique for solving the problem of unit commitment in any electric utility is presented in this paper. The effectiveness of economic dispatch is well understood when the objective is to schedule the committed generators to meet the load, maintain voltages and frequency within prescribed tolerances and minimize operating cost without unduly stress...

in this study, several data-driven techniques including system identification, adaptive neuro-fuzzy inference system (anfis), artificial neural network (ann) and wavelet-artificial neural network (wavelet-ann) models were applied to model rainfall-runoff (rr) relationship. for this purpose, the daily stream flow time series of hydrometric station of hajighoshan on gorgan river and the daily rai...

In a Wireless Sensor Network when an event is detected, the network traffic increases. It in turn increases the flow of data packets and congestion. Congestion in Wireless Sensor Network plays a vital role in degrading the performance of the network. Hence it necessitates, developing a novel technique to control congestion. In this paper, soft computing based congestion control technique is pro...

This paper presents a novel hybridization of the fuzzy logic, the neural network and the coevolutionary algorithm for building a fuzzy-neural system (or a Mamdani fuzzy system) from data. The novel hybridization uses the coevolution of many species, and proposes the coevolution of groups of similar species, both for the optimization of the structure of the fuzzy-neural network. In the fuzzy-neu...

Tool failure may result in losses in surface finish and dimensional accuracy of a finished part, or possible damage to the work piece and machine. This paper presents a Fuzzy Neural Network (FNN) which is designed and developed for machinery prognostic monitoring. The FNN is basically a multi-layered fuzzy-rule-based neural network which integrates a fuzzy logic inference into a neural network ...

-Intrusion Detection System is used to detect the unwanted activities over the network and to design IDS soft computing techniques are used. This paper describes the role of Artificial Neural Network, Fuzzy Logic and Genetic Algorithm in Intrusion Detection System. The artificial neural network learning algorithms, data retrieval using fuzzy logic under uncertainty and power of Genetic algorith...