The paper proposes the use of some stochastic methods in order to explain the presence of the critical points in macroeconomic time series, starting from the classical linear model input-output elaborated by W. Leontief. The development of the model (N. GeorgescuRoegen, 1971) yields the set of the linear differential equations describing the dynamics of a system containing two or more interdepe...

rational functions are of great interest to engineers and geoscientists. the rational polynomial coefficient (rpc) model as a generalized sensor model has been introduced as an alternative for the rigorous sensor model of the satellite imaging. numerical instability of normal equations is the only single obstacle to the implementation of these functions. practically, estimating rational functio...

comparison of linear and nonlinear (bilinear) time series models in reference crop evapotranspiration prediction in urmia synoptic stationreference crop evapotranspiration (eto) prediction is one of the important elements in optimizing agricultural water consumption. in this regard, one of the prediction approaches is to use the stochastic time series methods. in this research, ar (p) and arma(...

This paper presents a recursive linear convolving method to performe anisotropic diffusion in images. The proposed method based on the linear filtering technique gives an useful evolving interface in boundary propagating. The novel approach is that there is not need to estimate local and global properties previously of the concerned propagating boundary, it making a fast algorithm. However thes...

an alumina supported co/ni catalyst was prepared by sol-gel procedure to study the catalytic behavior during fischer-tropsch synthesis in a fixed-bed reactor. the effect of co conversion (10-50%) on hydrocarbon product distribution (ch4, c5+ and c2-c4 olefin selectivities) was studied. selectivity for ch4 decreased, while those of c5+ and olefin selectivities increased with increasing co conver...

this paper presents a prediction model based on a new neuro-fuzzy algorithm for estimating time in construction projects. the output of the proposed prediction model, which is employed based on a locally linear neuro-fuzzy (llnf) model, is useful for assessing a project status at different time horizons. being trained by a locally linear model tree (lolimot) learning algorithm, the model is int...

We study a model in which individual agents use simple linear first order price forecasting rules, adapting them to the complex evolving market environment with a smart Genetic Algorithm optimization procedure. The novelties are: (1) a parsimonious experimental foundation of individual forecasting behaviour; (2) an explanation of individual and aggregate behavior in four different experimental ...

This paper presents a model for Collective Free Improvisation (CFI), a form of improvisation that can be defined as referent-free. While very simple, it captures some interesting mechanisms of CFI. We use two variables: the intention and the objective. Both variables are used to describe the production and organization of the improvisers’ signals. Using a system of Landau equations, we propose ...

This paper introduces an extension of linear temporal logic that allows to express properties about systems that are composed of entities (like objects) that can refer to each other via pointers. Our logic is focused on specifying properties about the dynamic evolution (such as creation, adaptation, and removal) of such pointer structures. The semantics is based on automata on infinite words, e...

A computational framework is presented for the simulation of eukaryotic cell migration and chemotaxis. An empirical pattern formation model, based on a system of non-linear reaction-diffusion equations, is approximated on an evolving cell boundary using an Arbitrary Lagrangian Eulerian surface finite element method (ALE-SFEM). The solution state is used to drive a mechanical model of the protru...