The proliferation of wireless multihop networks has made various operations, such as search and retrieval of distributed data a significant concern. Various methods have been proposed for performing such tasks efficiently, especially when all network nodes need to be visited at least once. Random walks are probabilistic approaches for performing the aforementioned operations effectively and wit...

Possibilistic networks and possibilistic logic bases are important tools to deal with uncertain pieces of information. Both of them offer a compact representation of possibility distributions. This paper studies a new representation format, called hybrid possibilistic networks, which cover both standard possibilistic networks and possibilistic knowledge bases. An adaptation of propagation algor...

A high performance speaker-independent isolated-word hybrid speech recognizer was developed which combines Hidden Markov Models (HMMs) and Radial Basis Function (RBF) neural networks. In recognition experiments using a speaker-independent E-set database, the hybrid recognizer had an error rate of 11.5% compared to 15.7% for the robust unimodal Gaussian HMM recognizer upon which the hybrid syste...

A high performance speaker-independent isolated-word hybrid speech recognizer was developed which combines Hidden Markov Models (HMMs) and Radial Basis Function (RBF) neural networks. In recognition experiments using a speaker-independent E-set database, the hybrid recognizer had an error rate of 11.5% compared to 15.7% for the robust unimodal Gaussian HMM recognizer upon which the hybrid syste...

In this paper obligatory hybrid networks of evolutionary processors (a variant of hybrid networks of evolutionary processors model) are proposed. In the obligatory hybrid network of evolutionary processors a node discards the strings to which no operations are applicable. We show that such networks have the same computability power as Turing machines only using one operation per node (deletion ...

Estimation (Forecasting) of industrial production costs is one of the most important factor affecting decisions in the highly competitive markets. Thus, accuracy of the estimation is highly desirable. Hibrid Regression Neural Network is an approach proposed in this paper to obtain better fitness in comparison with Regression Analysis and the Neural Network methods. Comparing the estimated resul...

This paper presents a comparative study of the hybrid models, neural networks and nonparametric regression models in time series forecasting. The components of these hybrid models are consisting of the nonparametric regression and artificial neural networks models. Smoothing spline, regression spline and additive regression models are considered as the nonparametric regression components. Furth...

The increased using of the Internet and its accelerated growth leads to reduced network bandwidth and the capacity of servers; therefore, the quality of Internet services is unacceptable for users while the efficient and effective delivery of content on the web has an important role to play in improving performance. Content distribution networks were introduced to address this issue. Replicatin...

The combination of the emerging Digital Video Broadcasting – Handheld (DVB-H) standard with cellular communication like UMTS produces a hybrid network with enormous potential for mobile multimedia applications. In order to optimize the performance of hybrid networks, the characteristics of different individual networks have to be considered. Our prototypical hybrid network infrastructure employ...