PMID- 18188992
OWN - NLM
STAT- MEDLINE
DCOM- 20080228
LR  - 20191210
IS  - 0895-3988 (Print)
IS  - 0895-3988 (Linking)
VI  - 20
IP  - 5
DP  - 2007 Oct
TI  - Prediction of anoxic sulfide biooxidation under various HRTs using artificial 
      neural networks.
PG  - 398-403
AB  - OBJECTIVE: During present investigation the data of a laboratory-scale anoxic 
      sulfide oxidizing (ASO) reactor were used in a neural network system to predict 
      its performance. METHODS: Five uncorrelated components of the influent wastewater 
      were used as the artificial neural network model input to predict the output of 
      the effluent using back-propagation and general regression algorithms. The best 
      prediction performance is achieved when the data are preprocessed using principal 
      components analysis (PCA) before they are fed to a back propagated neural 
      network. RESULTS: Within the range of experimental conditions tested, it was 
      concluded that the ANN model gave predictable results for nitrite removal from 
      wastewater through ASO process. The model did not predict the formation of 
      sulfate to an acceptable manner. CONCLUSION: Apart from experimentation, ANN 
      model can help to simulate the results of such experiments in finding the best 
      optimal choice for ASObased denitrification. Together with wastewater collection 
      and the use of improved treatment systems and new technologies, better control of 
      wastewater treatment plant (WTP) can lead to more effective maneuvers by its 
      operators and, as a consequence, better effluent quality.
FAU - Mahmood, Qaisar
AU  - Mahmood Q
AD  - Department of Environmental Engineering, College of Environment and Resource 
      Science, Zhejiang University, Hangzhou 310029, Zhejiang, China.
FAU - Zheng, Ping
AU  - Zheng P
FAU - Wu, Dong-Lei
AU  - Wu DL
FAU - Wang, Xu-Sheng
AU  - Wang XS
FAU - Yousaf, Hayat
AU  - Yousaf H
FAU - Ul-Islam, Ejaz
AU  - Ul-Islam E
FAU - Hassan, Muhammad Jaffar
AU  - Hassan MJ
FAU - Jilani, Ghulam
AU  - Jilani G
FAU - Azim, Muhammad Rashid
AU  - Azim MR
LA  - eng
PT  - Journal Article
PL  - China
TA  - Biomed Environ Sci
JT  - Biomedical and environmental sciences : BES
JID - 8909524
RN  - 0 (Sulfates)
RN  - 0 (Sulfides)
SB  - IM
MH  - Bioreactors
MH  - *Neural Networks, Computer
MH  - Oxidation-Reduction
MH  - Sulfates/chemistry
MH  - Sulfides/*chemistry
MH  - Time Factors
MH  - Waste Disposal, Fluid/*methods
EDAT- 2008/01/15 09:00
MHDA- 2008/02/29 09:00
CRDT- 2008/01/15 09:00
PHST- 2008/01/15 09:00 [pubmed]
PHST- 2008/02/29 09:00 [medline]
PHST- 2008/01/15 09:00 [entrez]
PST - ppublish
SO  - Biomed Environ Sci. 2007 Oct;20(5):398-403.