We introduce and analyze a new mixed finite element method with reduced symmetry for the standard linear model in viscoelasticity. Following previous approach employed elastodynamics, present problem is formulated as second-order hyperbolic partial differential equation which, after using motion to eliminate displacement unknown, stress tensor remains main variable be found. The resulting varia...

in the present study, the energetic and economic modeling of lentil and chickpea production in esfahan province of iran was conducted using adaptive neuro-fuzzy inference system (anfis) and linear regression. data were taken by interviewing and visiting of 140 lentil farms and 110 chickpea farms during 2014-2015 production period. the results showed that the yield and total energy consumption w...

evolving models have found applications in many real world systems. in this paper, potentials of the evolving linear models (elms) in tracking control design for nonlinear variable structure systems are introduced. at first, an elm is introduced as a dynamic single input, single output (siso) linear model whose parameters as well as dynamic orders of input and output signals can change through ...

spatial-temporal modeling of air pollutants, ground-level ozone concentrations in particular, has attracted recent attention because by using spatial-temporal modeling, can analyze, interpolate or predict ozone levels at any location. in this paper we consider daily averages of troposphere ozone over tehran city. for eliminating the trend of data, a dynamic linear model is used, then some featu...

We give an algorithm for deciding E-uniication problems for linear standard equational theories (linear equations with all shared variables at a depth less than two) and varity 1 goals (linear equations with no shared variables). We show that the algorithm halts in quadratic time for the non-uniform E-uniication problem, and linear time if the equational theory is varity 1. The algorithm is sti...

This paper introduces discretionary imprecise data in Data Envelopment Analysis (DEA) and discusses the efficiency evaluation of Decision Making Units (DMUs) with non-discretionary imprecise data. Then, suggests a method for evaluation the efficiency of DMUs with non-discretionary imprecise data. When some inputs and outputs are imprecise and non-discretionary, the DEA model becomes non-linear ...

land use optimization using linear programing is a method in watershed management for access to production sustainability and decreasing of soil erosion. the sensitivity analysis of the model can with investigation of results influence form changes in input parameters, lead to decrease the uncertainty in decision-making of management programs. so in this research, linear programming model using...