A methodology for sequencing batch reactor identification with artificial neural networks: A case study

Computers and Chemical Engineering

Volumn 33, Issue 2, 2009, Pages 465-472

  Aguado, D ^a   Ribes, J ^b   Montoya, T ^a   Ferrer, J ^a   Seco, A ^b  

^a UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

^b UNIVERSITY OF VALENCIA   (Spain)

Author keywords

Artificial neural networks; Sequencing batch reactor; Soft sensor

Indexed keywords

BACKPROPAGATION; BATCH REACTORS; BIOLOGICAL WATER TREATMENT; CUSTOMER SATISFACTION; PHOSPHORUS; QUALITY CONTROL; SENSOR NETWORKS; SENSORS; WASTEWATER;

ARTIFICIAL NEURAL NETWORKS; CASE STUDIES; CONTROL QUALITIES; DEVELOPED MODELS; ELECTRONIC SENSORS; ENHANCED BIOLOGICAL PHOSPHORUS REMOVALS; EXPERIMENTAL CONDITIONS; GENERALIZATION ABILITIES; INPUT DATUMS; LABORATORY ANALYSIS; LINE PREDICTIONS; MEASUREMENT PROCEDURES; NUTRIENT REMOVALS; OPTIMAL ARCHITECTURES; OPTIMAL LENGTHS; PHOSPHORUS CONCENTRATIONS; PREDICTIVE TOOLS; PROCESS REQUIREMENTS; SEQUENCING BATCH REACTOR; SOFT-SENSOR; SOLIDS RETENTION TIMES; SYSTEMATIC METHODOLOGIES; VARIABLE DYNAMICS;

NEURAL NETWORKS;

EID: 58249091983     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compchemeng.2008.10.018     Document Type: Article

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