Field of system identification have become important discipline. Identification is basically the process of developing or improving a mathematical representation of a physical system using experimental data. The artificial neural network is a newly developed technique among the identification methods. Dynamic function mapping, including the structural dynamic model is still a challenging topic ...

rapid urban growth is resulting into increase in travel demand and private vehicle ownership in urban areas. in the present scenario the existing infrastructure has failed to match the demand that leads to traffic congestion, vehicular pollution and accidents. with traffic congestion augmentation on the road, delay of commuters has increased and reliability of road network has decreased. four s...

Feature Markov Decision Processes (ΦMDPs) [Hut09] are well-suited for learning agents in general environments. Nevertheless, unstructured (Φ)MDPs are limited to relatively simple environments. Structured MDPs like Dynamic Bayesian Networks (DBNs) are used for large-scale realworld problems. In this article I extend ΦMDP to ΦDBN. The primary contribution is to derive a cost criterion that allows...

Who are the influential people in an online social network? The answer to this question depends not only on the structure of the network, but also on details of the dynamic processes occurring on it. We classify these processes as conservative and non-conservative. A random walk on a network is an example of a conservative dynamic process, while information spread is non-conservative. The influ...

In competitive markets, market segmentation is a critical point of business, and it can be used as a generic strategy. In each segment, strategies lead companies to their targets; thus, segment selection and the application of the appropriate strategies over time are very important to achieve successful business. This paper aims to model a strategy-aligned fuzzy approach to market segment ev...

Dynamic Bayesian networks (DBN) are a popular framework for managing uncertainty in time-evolving systems. Their efficient learning has thus received many contributions in the literature. But, most often, those assume that the data to be modeled by a DBN are generated by a stationary process, i.e., neither the structure nor the parameters of the BNs evolve over time. Unfortunately, there exist ...

service oriented architecture (soa) technology enables composition of large and complex computational units out of the available atomic services. implementation of soa brings about challenges which include service discovery, service interaction, service composition, robustness, quality of service, security, etc. these challenges are mainly due to the dynamic nature of soa. soamay often need to ...