https://scholars.lib.ntu.edu.tw/handle/123456789/448903
Title: | Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks | Authors: | Chiang Y.-M. Chang L.-C. Tsai M.-J. Wang Y.-F. FI-JOHN CHANG |
Issue Date: | 2011 | Journal Volume: | 15 | Journal Issue: | 1 | Start page/Pages: | 185-196 | Source: | Hydrology and Earth System Sciences | Abstract: | Pumping stations play an important role in flood mitigation in metropolitan areas. The existing sewerage systems, however, are facing a great challenge of fast rising peak flow resulting from urbanization and climate change. It is imperative to construct an efficient and accurate operating prediction model for pumping stations to simulate the drainage mechanism for discharging the rainwater in advance. In this study, we propose two rule-based fuzzy neural networks, adaptive neuro-fuzzy inference system (ANFIS) and counterpropagation fuzzy neural network for on-line predicting of the number of open and closed pumps of a pivotal pumping station in Taipei city up to a lead time of 20 min. The performance of ANFIS outperforms that of CFNN in terms of model efficiency, accuracy, and correctness. Furthermore, the results not only show the predictive water levels do contribute to the successfully operating pumping stations but also demonstrate the applicability and reliability of ANFIS in automatically controlling the urban sewerage systems. © Author(s) 2011. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/448903 | ISSN: | 1027-5606 | DOI: | 10.5194/hess-15-185-2011 | SDG/Keyword: | Adaptive neuro-fuzzy inference system; Auto-control; Counter propagation; Flood mitigation; Leadtime; Metropolitan area; Model efficiency; Peak flows; Prediction model; Pumping operations; Pumping stations; Rule-based Fuzzy neural networks; Sewerage system; Climate change; Fuzzy inference; Fuzzy systems; Mathematical models; Pumping plants; Pumps; Sewers; Water levels; Fuzzy neural networks; accuracy assessment; artificial neural network; climate change; control system; drainage network; flood; fuzzy mathematics; metropolitan area; mitigation; model validation; numerical model; peak flow; performance assessment; pumping; rainwater; reliability analysis; sewer network; urban area; urbanization; water level |
Appears in Collections: | 生物環境系統工程學系 |
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