the paper deals with data envelopment analysis (dea) and artificial neural network (ann). we believe that solving for the dea efficiency measure, simultaneously with neural network model, provides a promising rich approach to optimal solution. in this paper, a new neural network model is used to estimate the inefficiency of dmus in large datasets.

this paper presents a hybrid approach to developing a short-term traffic flow prediction model. in thisapproach a primary model is synthesized based on neural networks and then the model structure is optimized throughgenetic algorithm. the proposed approach is applied to a rural highway, ghazvin-rasht road in iran. the obtainedresults are acceptable and indicate that the proposed approach can i...

predicting the maintenance and management costs and replacement age of tractors in agricultural mechanized units, is important from several points. so, doing a timely agricultural operations, more accurate measure of the amount of income  including the cost of these items , determining the useful life of old tractors , replacement age, cost of the process changes and the possibility of examinin...

background: we designed an algorithmic model based on the logistic regression analysis and a non-algorithmic model based on the artificial neural network (ann). materials and methods: the ability of these models was compared together in clinical application to differentiate malignant from benign breast tumors in a study group of 161 patients' records. each patient’s record consisted of 6 s...

infiltration rate is one of the most important soil physical parameters and is a basic input data in irrigation and drainage projects. although, a number of theoretical or experimental based equations are presented to describe this phenomenon but the evaluation of some new sciences such as artificial neural networks, for prediction of the phenomenon can be investigated. generally, the infiltrat...

the prediction of the joint angle position, especially during tremor bursts, can be useful for detecting, tracking, and forecasting tremors. thus, this research proposes a new model for predicting the wrist joint position during rhythmic bursts and inter‑burst intervals. since a tremor is an approximately rhythmic and roughly sinusoidal movement, neural oscillators have been selected to underli...

background: one issue of concern in water supply is the quality of water. measuring the qualitative parameters of water is time-consuming and costly. predicting these parameters using various models leads to a reduction in related expenses and the presentation of overall and comprehensive statistics for water resource management. methods: the present study used an artificial neural network (ann...

this article deals with the issues associated with developing a new design methodology for the nonlinear model-predictive control (mpc) of a chemical plant. a combination of multiple neural networks is selected and used to model a nonlinear multi-input multi-output (mimo) process with time delays.  an optimization procedure for a neural mpc algorithm based on this model is then developed. the p...

objective: social anxiety disorder (sad) is defined as a constant fear of being embarrassed or negatively evaluated in social situations or while doing activities in the presence of others. several studies have examined the role of certain variables that might predict response to treatment and may affect treatment outcome. the purpose of this study was to identify predictive variables of change...