Civil Engineering and Environmental Systems · 2001 · 32 citations · 18 references
EngineeringEnvironmental EngineeringArtificial IntelligenceProcess ControlWastewater TreatmentBioprocess ControlController DesignEvolutionary ComputationGenetic AlgorithmsIndustrial Wastewater TreatmentNeural Control SystemsControl Algorithm DevelopmentControl AlgorithmsGenetic Algorithm OptimizationIntelligent ControlNeural Network ControlWastewater Treatment PlantsWastewater Treatment Processes
Abstract The successful operation of wastewater treatment plants involves many uncertain factors. Not only the physical and chemical properties of wastewater streams but also the complexity of biological mechanism would significantly influence the performance of treatment process. Due to the rising concerns of environmental and economic impacts, improved control algorithms, using artificial intelligence technologies, have gradually received wide attention in the scientific community. This paper develops a genetic algorithm-based neural network for the assistance of intelligent controller design. An industrial wastewater treatment plant in Taiwan verified the applicability of such a methodology. The hybrid intelligent control technology applied in this paper is suitable to many other types of wastewater treatment plants by a slightly modified concept. Keywords: Optimal controlGenetic algorithmsNeural networkWastewater treatmentArtificial intelligenceSoft computing Additional informationNotes on contributorsNI-BIN CHANG Corresponding author, e-mail: al211@mail.ncku.edu.tw
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