the aim followed in this study was to compare the performance of multiple regression vs neural network models to predict the activity of antioxidant enzymes super oxide dismutase (sod), cat alase (cat), ascorbate pero xidase (apx) and peroxidase (pox) in the shoots of wheat (triticum aestivum), alvand cultivar in a soil polluted with cadmium. the treatments consisted of four levels of cadmium (...

information on nitrate in groundwater resources requires periodic measurements are accurate. despite the measure in some areas due to sensitive social and health community are not reported. therefore, be informed of the status of each area of water quality, modeling is essential. the purpose of this study was the application of artificial neural network method for estimating nitrate and compare...

In this study, an intelligent control scheme is developed for induction motors (IMs). The dynamics of IMs are unknown and perturbed by the variation rotor resistance load changes. system has two stages. identification stage, group method data-handling (GMDH) neural network (NN) was designed online modeling IM. GMDH-NN applied to compensate impacts disturbances uncertainties. stability shown Lya...

investigation of soil properties like cation exchange capacity (cec) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. pedotransfer functions (ptfs) provide an alternative by estimating soil parameters from more readily available soil data...

In this paper, we present a recurrent neural network model for solving CCR Model in Data Envelopment Analysis (DEA). The proposed neural network model is derived from an unconstrained minimization problem. In the theoretical aspect, it is shown that the proposed neural network is stable in the sense of Lyapunov and globally convergent to the optimal solution of CCR model. The proposed model has...

This survey deals with up-to-date results in the field of hybrid algorithms development of GMDH-type Neural Networks (GMDH-NN) and other methods of Artificial Intelligence (AI) which are successfully used for solving complex economic problems. Such hybrid algorithms are now only in its early stage of active research. General characteristics and main weaknesses of GMDH-NN are firstly presented. ...