Back Propagation Neural Network Model for Predicting the Performance of Immobilized Cell Biofilters Handling Gas-Phase Hydrogen Sulphide and Ammonia

<table>Effect of inlet loading rate on the elimination capacity and removal efficiency profiles of the immobilized cell biofilter handling NH<sub>3</sub> vapors (More details can be seen in [<a href="/journals/bmri/2013/463401/#B2">2</a>]).</table>

BioMed Research International

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Figure 2: Back Propagation Neural Network Model for Predicting the Performance of Immobilized Cell Biofilters Handling Gas-Phase Hydrogen Sulphide and Ammonia 

Figure 2 | Back Propagation Neural Network Model for Predicting the Performance of Immobilized Cell Biofilters Handling Gas-Phase Hydrogen Sulphide and Ammonia 