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 H<sub>2</sub>S vapors (More details can be seen in [<a href="/journals/bmri/2013/463401/#B3">3</a>]).</table>

BioMed Research International

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Figure 1: Back Propagation Neural Network Model for Predicting the Performance of Immobilized Cell Biofilters Handling Gas-Phase Hydrogen Sulphide and Ammonia 

Figure 1 | Back Propagation Neural Network Model for Predicting the Performance of Immobilized Cell Biofilters Handling Gas-Phase Hydrogen Sulphide and Ammonia 