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 (...

Genetic programming has been widely used in the engineering field. Compared with the conventional genetic programming and artificial neural network, geometric semantic genetic programming (GSGP) is superior in astringency and computing efficiency. In this paper, GSGP is adopted for the classification and regression analysis of a sample dataset. Furthermore, a model for slope stability analysis ...

in general, amount of sludge will definitely increase in near future and composting processes, optimum composting conditions and compost use as fertilizer and soil amendment will then be significant research topics. the present study was conducted for o2 parameter estimation by multiple regression and artificial neural networks methods. daily temperature, ch4, h2s, co2 and o2 measurements were ...

The purpose of this study is to optimize the stock price forecasting model with meta-innovation method in pharmaceutical companies.In this research, stock portfolio optimization has been done in two separate phases.The first phase is related to forecasting stock futures based on past stock information, which is forecasting the stock price using artificial neural network.The neural network used ...

The excavation damaged zone (EDZ) can be defined as a rock zone where the rock properties and conditions have been changed due to the processes related to an excavation. This zone affects the behavior of rock mass surrounding the construction that reduces the stability and safety factor and increase probability of failure of the structure. In this paper, a methodology was examined for computing...

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with the increase of the volume of information and the progress in technology, the deficiency of traditional algorithms for fast information retrieval becomes more clear. when large volumes of data are to be handled, the use of neural network as an artificial intelligent technique is a suitable method to increase the information retrieval speed. neural networks present a suitable representation...

In this work, an artificial neural network (ANN) model along with a combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) i.e. (PSO-ANFIS) are proposed for modeling and prediction of the propylene/propane adsorption under various conditions. Using these computational intelligence (CI) approaches, the input parameters such as adsorbent shape (S<su...