نتایج جستجو برای: ann model
تعداد نتایج: 2121695 فیلتر نتایج به سال:
The adsorption ability of Dowex Optipore L493 resin modified with Aliquat 336 (MR), activated carbon modified with Aliquat 336 (MAC) and sawdust modified with Aliquat 336 (MS) for removal of Cr(VI) from aqueous solution in batch system was investigated. The effects of operational parameters such as adsorbent dosage, initial concentration of Cr(VI) ions, pH, temperature and contact time were stu...
determining the distribution of heavy metals in groundwater is important in developing appropriate management strategies at mine sites. in this paper, the application of artificial intelligence (ai) methods to data analysis,namely artificial neural network (ann), hybrid ann with biogeography-based optimization (ann-bbo), and multi-output adaptive neural fuzzy inference system (manfis) to estima...
in this study, a hybrid intelligent model has been designed to predict groundwater inflow to a mine pit during its advance. novel hybrid method coupling artificial neural network (ann) with genetic algorithm (ga) called ann-ga, was utilised. ratios of pit depth to aquifer thickness, pit bottom radius to its top radius, inverse of pit advance time and the hydraulic head (hh) in the observation w...
Accurate estimation of river flows is one of the fundamental activities in water resources management of river basins. Artificial neural network (ANN) and support vector machine (SVM) are the most important data mining models that can be considered for this purpose. Due to the data-based attribute of these models, probability distribution of data may have a considerable effects on their pe...
Simulation and prediction of CO2 laser cutting of Perspex glass has been done by feed forward back propagation Artificial Neural Network (ANN). Experimental data of Taguchi orthogonal array L9 was used to train the ANN model. The simulation results were evaluated and verified with the experiment. In some cases, the prediction errors of Taguchi ANN model was larger than 10% even with Levenberg M...
Developing models for accurate natural gas spot price forecasting is critical because these forecasts are useful in determining a range of regulatory decisions covering both supply and demand of natural gas or for market participants. A price forecasting modeler needs to use trial and error to build mathematical models (such as ANN) for different input combinations. This is very time consuming ...
This paper presents artificial neural network (ANN)-based models for forecasting precipitation, in which the training parameters are adjusted using a parameter automatic calibration (PAC) approach. A classical ANN-based model, the multilayer perceptron (MLP) neural network, was used to verify the utility of the proposed ANN–PAC approach. The MLP-based ANN used the learning rate, momentum, and n...
Comparisons made between the measured data carried out from September to December 2012 using a streamer trap and the results of some semi-empirical formulas including C.E.R.C, Walton and Bruno (W.B), van der Meer (V), Kamphuis (K), and an Artificial Neural Network (ANN) model. Six dominant variables are considered in the ANN model to estimate long-shore sediment transport rate. Results reveal t...
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