Gross parameters prediction of a granular-attached biomass reactor by means of multi-objective genetic-designed artificial neural networks: touristic pressure management case

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• 作者：G. Del Moro ; E. Barca ; M. De Sanctis…
• 关键词：Artificial neural networks ; Fixed ; bed bioreactors ; Predictive models ; Wastewater treatment ; Touristic pressure
• 刊名：Environmental Science and Pollution Research
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：23
• 期：6
• 页码：5549-5565
• 全文大小：2,715 KB
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• 作者单位：G. Del Moro (1)
  E. Barca (1)
  M. De Sanctis (1)
  G. Mascolo (1)
  C. Di Iaconi (1)
  
  1. Istituto di Ricerca Sulle Acque, Consiglio Nazionale delle Ricerche, Viale F. De Blasio 5, 70132, Bari, Italy
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Environment
  Environment
  Atmospheric Protection, Air Quality Control and Air Pollution
  Waste Water Technology, Water Pollution Control, Water Management and Aquatic Pollution
  Industrial Pollution Prevention
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1614-7499

文摘

The Artificial Neural Networks by Multi-objective Genetic Algorithms (ANN-MOGA) model has been applied to gross parameters data of a Sequencing Batch Biofilter Granular Reactor (SBBGR) with the aim of providing an effective tool for predicting the fluctuations coming from touristic pressure. Six independent multivariate models, which were able to predict the dynamics of raw chemical oxygen demand (COD), soluble chemical oxygen demand (COD_sol), total suspended solid (TSS), total nitrogen (TN), ammoniacal nitrogen (N–NH₄ +) and total phosphorus (P_tot), were developed. The ANN-MOGA software application has shown to be suitable for addressing the SBBGR reactor modelling. The R 2 found are very good, with values equal to 0.94, 0.92, 0.88, 0.88, 0.98 and 0.91 for COD, COD_sol, N–NH₄ +, TN, P_tot and TSS, respectively. A comparison was made between SBBGR and traditional activated sludge treatment plant modelling. The results showed the better performance of the ANN-MOGA application with respect to a wide selection of scientific literature cases.