a wind farm is a collection of wind turbines built in an area to provide electricity. wind power is a renewable energy resource and an alternative to non-renewable fossil fuels. in this paper impact of wind farms in power system reliability is investigate and a new procedure for reliability assessment of wind farms in hl1 level is proposed. in proposed procedure, application of fuzzy – markov f...

A wind farm is a collection of wind turbines built in an area to provide electricity. Wind power is a renewable energy resource and an alternative to non-renewable fossil fuels. In this paper impact of wind farms in power system reliability is investigate and a new procedure for reliability assessment of wind farms in HL1 level is proposed. In proposed procedure, application of Fuzzy – Markov f...

Prediction is a critical component in decision-making process for business management. Fuzzy Markov model is a common approach for dealing with the prediction of time series. However, not many studies devoted their attention to the effect of the parameters on model fitting for fuzzy Markov model. In the paper, we examine the prediction ability for fuzzy Markov model, based on the data of Taiwan...

In this paper, we present a fuzzy logic integration to the Hidden Markov Models (HMM). We have replaced the basic arithmetic operators by some adequate k z y operators. Using fuzzy operators permits us to relax the additivity constraint of probability measures. So we will need only the monotonicity with respect to set inclusion. Some results show the interest of our approach.

This paper presents a new method for fuzzy system reliability analysis based on fuzzy semi-markov model with fuzzy transitions. The definition and the basic equation for interval transitions of a semi-markov model with fuzzy transitions are provided. The transitions for the above model with fuzzy states is provided for the non-homogeneous case. We apply this fuzzy technique to ATM transactions ...

This is the first paper in a series of two papers describing a novel generalization of classical hidden Markov models using fuzzy measures and fuzzy integrals. In this paper, we present the theoretical framework for the generalization and, in the second paper, we describe an application of the generalized hidden Markov models to handwritten word recognition. The main characteristic of the gener...

This is the first paper in a series of two papers describing a novel generalization of classical hidden Markov models using fuzzy measures and fuzzy integrals. In this paper, we present the theoretical framework for the generalization and, in the second paper, we describe an application of the generalized hidden Markov models to handwritten word recognition. The main characteristic of the gener...

Gibbs distribution is used to represent fuzzy codebooks of individual speakers. The method of fuzzy evolutionary programming is employed to create the fuzzy codebooks and also to train hidden Markov models of speakers. This method increases the chance of attaining global maxima in Baum-Welch algorithm for hidden Markov model re-estimation. The experiments show the results of speaker identificat...

In this paper we introduce a new model for granular synthesis using Markov Chains and Fuzzy Sets. Whereas Markov Chains are used to control the evolution of the sound in time, Fuzzy Sets are employed to define the internal structure of the sound grains. We provide the mathematical foundations of the model and briefly discuss the implementation of a demonstration.

Industrial forecasting is a top-echelon research domain, which has over the past several years experienced highly provocative research discussions. The scope of this research domain continues to expand due to the continuous knowledge ignition motivated by scholars in the area. So, more intelligent and intellectual contributions on current research issues in the accident domain will potentially ...