The purpose of this paper is to advocate and encourage the application of fuzzy-neuro algorithms in the risk assessment of Distributed Real-Time (DRT) systems, where object-oriented and formal techniques by means of UML-SDL models are used as knowledge (data) providers to the fuzzy-neuro analyser. The paper includes an introductory description of DRT systems and the presentation of the UML and ...

in this paper, a novel neuro-fuzzy based method combined with a feature selection technique is proposed for online dynamic voltage stability status prediction of power system. this technique uses synchronized phasors measured by phasor measurement units (pmus) in a wide-area measurement system. in order to minimize the number of neuro-fuzzy inputs, training time and complication of neuro-fuzzy ...

In this thesis neuro-fuzzy methods for data analysis are discussed. We consider data analysis as a process that is exploratory to some extent. If a fuzzy model is to be created in a data analysis process it is important to have learning algorithms available that support this exploratory nature. This thesis systematically presents such learning algorithms, which can be used to create fuzzy syste...

The identi"cation and simulation of dynamic systems is still a challenging problem. In this article some basic aspects of neuro-fuzzy techniques for the identi"cation and simulation of time-dependent physical systems are presented. In particular, a neuro-fuzzy model that can be used for the identi"cation and the (real-time) simulation of viscoelastic models, is described. The presented model is...

In this study, the efficiency of neuro-fuzzy inference system (ANFIS) and genetic expression programming (GEP) in predicting the transfer length of prestressing strands in prestressed concrete beams was investigated. Many models suggested for the transfer length of prestressing strands usually consider one or two parameters and do not provide consistent accurate prediction. The alternative appr...

This paper addresses about an approach that suggests for stock portfolio optimization using the combination of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Capital Asset Pricing Model (CAPM). Stock portfolio optimization aims to determine which of the stocks to be added to a portfolio based on the investor’s needs, changing economic and market conditions. In order to construct an efficient...

A neuro-fuzzy modeling for forecasting the future dynamical behavior in vibration testing during satellite qualification is proposed in this paper. Vibration testing is employed for emulating vibrations present during the lifetime launching. There are different levels of excitation during vibration testing in order to verify and assure that the satellite and their sub-systems will support the e...

It is known that neuro-fuzzy system is easily stuck in local minimum. To improve these drawbacks, a two-stage algorithm combining the advantages of neuro-fuzzy and genetic algorithms (GA) is integrated in system identification. Genetic algorithms are general purposed optimization algorithms with adaptive reproduction, crossover, and mutation operators that provide a method to search optimal par...