This paper investigates how to develop a learning-based demand response approach for electric water heater in a smart home that can minimize the energy cost of the water heater while meeting the comfort requirements of energy consumers. First, a learning-based, data-driven model of an electric water heater is developed by using a nonlinear autoregressive network with external input (NARX) using...

Myxococcus xanthus fibril exopolysaccharide (EPS), essential for the social gliding motility and development of this bacterium, is regulated by the Dif chemotaxis-like pathway. DifA, an MCP homolog, is proposed to mediate signal input to the Dif pathway. However, DifA lacks a prominent periplasmic domain, which in classical chemoreceptors is responsible for signal perception and for initiating ...

Any discussion on exchange rate movements and forecasting should include explanatory variables from both the current account and the capital account of the balance of payments. In this paper, we include such factors to forecast the value of the Indian rupee vis a vis the US Dollar. Further, factors reflecting political instability and lack of mechanism for enforcement of contracts that can affe...

This paper deals with a new approach to detect the structure (i.e. determination of the number of hidden units) of a feedforward neural network (FNN). This approach is based on the principle that any FNN could be represented by a Volterra series such as a nonlinear inputoutput model. The new proposed algorithm is based on the following three steps: first, we develop the nonlinear activation fun...

This paper presents a new approach for modelling nonlinear dynamic processes (NDP). It is based on autoregressive with exogenous (NARX) inputs model structure and deep convolutional fuzzy system (DCFS). The DCFS hierarchical structure, which can overcome the deficiency of general systems when facing high dimensional data. For relieving curse dimensionality, as well improving approximation perfo...

Measurement of oil and gas two-phase flow with variable regimes relies to a large extent on patterns their transitions. Using multiphase flowmeters in flows high volume fractions is therefore usually associated uncertainties. This work presents dynamic neural network method measure the rate using nonlinear autoregressive exogenous inputs (NARX). Total temperature total pressure are used as obta...

Abstract This paper demonstrates the Gaussian process regression model's applicability combined with a nonlinear autoregressive exogenous (NARX) framework using experimental data measured PZTs' patches bonded in composite aeronautical structure for concerning novel SHM strategy. A stiffened carbon-epoxy plate regarding healthy condition and simulated damage on center of bottom part stiffener is...