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 ...

the rational expectations permanent income hypothesis implies that consumption follows a martingale. however, most empirical tests have rejected the hypothesis. those empirical tests are based on linear models. if the data generating process is non-linear, conventional tests may not assess some of the randomness properly. as a result, inference based on conventional tests of linear models can b...

Rios and Selinger have recently proposed a categorical model for the quantum programming language Proto-Quipper-M, which is an important fragment of the Quipper language. In this work, we describe an extension to their categorical model with the additional property that it is DCPOenriched, bringing us closer to modeling general recursion in the language. Similar to their model, our model exhibi...

in this study, application of adaptive neuro-fuzzy inference system (anfis) in forecasting three perspectives (1, 2, and 4 years) ahead of iran’s agricultural products export was compared with arima as the most common econometrics linear forecasting method. for this purpose, iran’s agricultural products export revenues related to 1959-2010, and forecast performance measures such as r2, mad, and...

a total number of 116,984 weight records belonging to 12,397 baluchi lambs reared in abbas abad breeding station during years 1978-2008 were used for phenotypic evaluation of maximum daily growth (mdg) and analysis of environmental factors affecting this trait. the initial data were performed by foxpro program and then gompertz non-linear model was fitted on the weight records of individual lam...

an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...