( ) A no®el generalized run-to-run control GR2R control strategy is presented for the optimization and control of nonlinear preparati®e chromatographic processes. The ( ) GR2R approach synergistically employs a hybrid both physical and empirical model to control chromatographic processes in the presence of sporadic and autocorrelated disturbances. First, parameters of the physical model through...

a two-factor experiment with interaction between factors wherein observations follow an inverse gaussian model is considered. analysis of the experiment is approached via an empirical bayes procedure. the conjugate family of prior distributions is considered. bayes and empirical bayes estimators are derived. application of the procedure is illustrated on a data set, which has previously been an...

A hybrid modeling approach that uses the parabolic equation (PE) with an empirical source model is presented to study and predict the underwater noise due to pile driving in shallow, inhomogeneous environments over long propagation ranges. The empirical source model uses a phased point source array to simulate the time-dependent pile source. The pile source is coupled with a broadband applicati...

in this paper two nodes to model isotropic and anisotropic media in transmission line matrix method (tlm) are presented. by using these two nodes, the permeability and permittivity of an anisotropic media can be modeled simultaneously. another application of these nodes is in modeling media with permittivity and permeability less than one. in the conventional 2 dimensional tlm, the stubs repres...

It is important for executives to predict the future trends. Otherwise, their companies cannot make profitable decisions and investments. The Bass diffusion model can describe the empirical adoption curve for new products and technological innovations. The Grey model provides shortterm forecasts using four data points. This study develops a combined model based on the rolling Grey model RGM and...

This paper deals with an option pricing model which can be thought of as a hybrid stochastic and local volatility model. This model is built on the local volatility term of the well-known constant elasticity of variance (CEV) model multiplied by a stochastic volatility term driven by a fast mean-reverting Ornstein-Uhlenbeck process. An asymptotic formula for European option price is derived to ...

This paper aims at proposing a quadratic assignment-based mathematical model to deal with the stochastic dynamic facility layout problem. In this problem, product demands are assumed to be dependent normally distributed random variables with known probability density function and covariance that change from period to period at random. To solve the proposed model, a novel hybrid intelligent algo...

rainfall-runoff modeling is most important component in the water resource management of river basins. the successful application of a conceptual rainfall-runoff model depends on how well it is calibrated. the degree of difficulty in solving the global optimization method is generally dependent on the dimensionality of the model and certain of the characteristics of object function. the purpose...

Physics-based numerical models designed to study processes on the surface of the Earth are commonly built with conservation laws. Yet conservations laws are based on a treatable subset of all physical and biological processes operating in the system of interest, and empirical relationships are always required to fully describe systems (and provide mathematical “closure”). In contrast to conserv...

We propose a hybrid learning approach to provide automated assistance for personalized product recommendation. The novel feature of this work is that the system learns and uses models of both user preferences and the user’s intentional context. Both learning types are based on the same user input, but elicit different aspects of the user model. User preference is learned via Support Vector Mach...