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2024_WRR.pdf ReportingModule: PDF-hul, Rel. 1.12.4 (2023-03-16) LastModified: 2025-11-18 03:59:44 CET Size: 683066 Format: PDF Version: 1.4 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 0 FreeObjects: 2 IncrementalUpdates: 0 DocumentCatalog: ViewerPreferences: HideToolbar: false HideMenubar: false HideWindowUI: false FitWindow: false CenterWindow: false DisplayDocTitle: false NonFullScreenPageMode: UseNone Direction: L2R ViewArea: CropBox ViewClip: CropBox PrintArea: CropBox PageClip: CropBox PageLayout: SinglePage PageMode: UseNone Language: en-US Outlines: Item: Title: Reducing the Environmental Impact of Sewer Network Overflows Using Model Predictive Control Strategy Children: Item: Title: Abstract Item: Title: 1. Introduction Item: Title: 2. Materials and Methods Children: Item: Title: 2.1. The Sewer Network Structure Item: Title: 2.2. The Influent of the Sewer Network Children: Item: Title: 2.2.1. The Forecasted Influent Item: Title: 2.2.2. The Disturbed Influent Item: Title: 2.3. The Mathematical Model of the Sewer Network Children: Item: Title: 2.3.1. Performance Indicators Item: Title: 2.4. Optimization of the Sewer Network Operation Using the Model Predictive Control Algorithm Children: Item: Title: 2.4.1. Model Predictive Control Formulation Item: Title: 2.4.2. Optimization Using Particle Swarm Optimization Method Item: Title: 2.4.3. Model Predictive Control Parameters Item: Title: 3. Results and Discussion Children: Item: Title: 3.1. Simulation Tests Children: Item: Title: 3.1.1. Case No. 1 Item: Title: 3.1.2. Case No. 2 Item: Title: 3.1.3. Case No. 3 Item: Title: 3.2. Computational Effort Item: Title: 4. Conclusions Item: Title: Data Availability Statement Item: Title: References Filters: FilterPipeline: FlateDecode FilterPipeline: DCTDecode Images: Image: NisoImageMetadata: FormatName: image/png ImageWidth: 228 ImageHeight: 45 ColorSpace: RGB BitsPerSample: 8 BitsPerSampleUnit: integer Filter: 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