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This discussion offers a systematic approach to predict the adsorption characteristics of a pharmaceutical pollutant, ibuprofen through artificial neural network. The artificial neural network is inspired by biological nervous system. Artificial neural networks are being extensively used for predicting the rate of adsorption of an adsorbent in solid-liquid adsorption system. Adsorption is a versatile method for the treatment of waste water bearing various pollutants. In case of batch adsorption study, the most significant output of an adsorption process, the adsorption capacity can be…mehr

Produktbeschreibung
This discussion offers a systematic approach to predict the adsorption characteristics of a pharmaceutical pollutant, ibuprofen through artificial neural network. The artificial neural network is inspired by biological nervous system. Artificial neural networks are being extensively used for predicting the rate of adsorption of an adsorbent in solid-liquid adsorption system. Adsorption is a versatile method for the treatment of waste water bearing various pollutants. In case of batch adsorption study, the most significant output of an adsorption process, the adsorption capacity can be predicted either by equilibrium study or kinetic study. But application of a new method for the prediction of ibuprofen adsorption is artificial neural network which bifurcates the conventional prediction methods. In the present investigation, the ibuprofen adsorption capacity of microwave assisted activated carbon was predicted through artificial neural network.
Autorenporträt
He is a Professor of Department of Chemical Engineering, Indian Institute of Technology Kharagpur,India. He has over 22 years of teaching and research experiences. His field of research is environmental pollution control. He has above 60 international publications. Monal Dutta is also associated with the same department as research scholar.