RFID technology has been recently adopted in retail environments to track consumer in-store movements, bringing about new exciting opportunities for spatial data mining-enabled marketing. In this paper, we propose a Dynamic Bayesian Networks (DBN)-based model of customer in-store shopping trips and activities. This model infers a customer's product purchase interest given the observations of cu...

This paper presents a new recurrent neural network (RNN) structure called ENEM for dynamic system identification. ENEM structure is based on Elman network and NARX neural network. In order to show the performance of ENEM for system identification, the results were also compared to the results of Elman network, Jordan network and their modified models. The identification results of linear and no...

In this paper we develop a method for identifying SISO Wiener-type nonlinear systems, that is, systems consisting of a linear dynamic system followed by a static nonlinearity. Unlike previous techniques developed for Wiener system identification, our approach allows the identification of systems with nonlinearities that are known but not necessarily invertible, continuous, differentiable, or an...

Nowadays the reliable availability of electricity is expected by both industrial and residential consumers. However, generation, transmission distribution all pose engineering challenges in adapting to consumers sustainable directives while maintaining operational safety. The increasing demand for on consumer side growing number renewable energy sources (RES) generation are supporting spread ca...