Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
The lead recovery prediction from lead concentrate by an artificial neural network and particle swarm optimization
Prediction of lead recovery during the leaching process is required to increase the process efficiency by proper modeling. In this study, a new artificial neural network predictive model based on the particle swarm optimization (ANN-PSO) was developed to predict the lead recovery by a hydrometallurgical method of lead concentrate leaching using fluoroboric acid. A multi-layer ANN-PSO model was trained for developing a predictive model based on the main effective parameters on the lead leaching process. The input parameters of the ANN-PSO model were leaching time, liquid/solid ratio, stirring speed, temperature and fluoroboric acid concentration, while the lead recovery during leaching was the output. The results indicate that the proposed ANN-PSO model can be effectively predicted the lead recovery during lead concentrate leaching using fluoroboric acid.
The lead recovery prediction from lead concentrate by an artificial neural network and particle swarm optimization
Prediction of lead recovery during the leaching process is required to increase the process efficiency by proper modeling. In this study, a new artificial neural network predictive model based on the particle swarm optimization (ANN-PSO) was developed to predict the lead recovery by a hydrometallurgical method of lead concentrate leaching using fluoroboric acid. A multi-layer ANN-PSO model was trained for developing a predictive model based on the main effective parameters on the lead leaching process. The input parameters of the ANN-PSO model were leaching time, liquid/solid ratio, stirring speed, temperature and fluoroboric acid concentration, while the lead recovery during leaching was the output. The results indicate that the proposed ANN-PSO model can be effectively predicted the lead recovery during lead concentrate leaching using fluoroboric acid.
The lead recovery prediction from lead concentrate by an artificial neural network and particle swarm optimization
Sobouti, Arash (Autor:in) / Hoseinian, Fatemeh Sadat (Autor:in) / Rezai, Bahram (Autor:in) / Jalili, Sara (Autor:in)
Geosystem Engineering ; 22 ; 319-327
02.11.2019
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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| British Library Online Contents | 2014