This paper explores the learning fuzzy inference systems implemented as adaptive fuzzy-neural networks. The research into application of learning techniques to fuzzy inference systems (FIS) has matured into a family of adaptive fuzzy inference systems (AFIS). In most cases, the learning FIS and AFIS families can be interpreted as a partially connected multilayer feedforward neural network with ...

The integration of neural networks and fuzzy inference systems could be formulated into three main categories: cooperative, concurrent and integrated neuro-fuzzy models. We present three different types of cooperative neuro-fuzzy models namely fuzzy associative memories, fuzzy rule extraction using self-organizing maps and systems capable of learning fuzzy set parameters. Different Mamdani and ...

Industrial Disputes cause loss of productivity and decrease of profit, tending towards huge losses. It is, therefore, necessary to establish a benchmark level of tact or skill that is required to ensure the prevention of Industrial Disputes. The benchmark level could be an empirical formula, or a set of regulatory data, that would be required to be satisfied. The procedure to be followed requir...

Functional equivalence of radial basis function (RBF) networks and a class of fuzzy inference systems is considered. The class of fuuy systems based on the Takagi-Sugeno model is referred to as TS-model of fuzzy inference. From the abstract mathematical viewpoint the functional equivalence between radial basis function networks and fuzzy inference systems is already shown. However, from the vie...

Pervasive computing allows data to be collected using sensors and mobile devices. Recent studies, however, show that in emergency and crisis situations conventional access control mechanisms are too rigid for information sharing. There is an increasing need to secure the information collected from the pervasive computing environments, and yet to be able to allow flexible data sharing to facilit...

Most of self-tuning fuzzy systems, which are automatically constructed from learning data, are based on the steepest descent method (SDM). However, this approach often requires a large convergence time and gets stuck into a shallow local minimum. One of its solutions is to use fuzzy rule modules with a small number of inputs such as DIRMs (Double-Input Rule Modules) and SIRMs (Single-Input Rule...

service availability is important for any organization. this has become more important with the increase of dos attacks. it is therefore essential to assess the threat on service availability. we have proposed a new model for threat assessment on service availability with a data fusion approach. we have selected three more important criteria for evaluating the threat on service availability and...