Abstract
Smart water construction is not only an important part of the development process of smart city, but also a key link in the implementation of urban people's livelihood guarantee. Urban water supply dispatching realizes artificial intelligence, which can carry out real-time dynamic control and ensure the stability of the overall water supply pattern. At the same time, it is also the primary platform for the most direct business connection between production technology management and grass-roots units. It also establishes channels for various sections in the field of urban water supply, such as engineering management, measurement management, water quality management, water plant technical measures management and so on. With the continuous innovation and development of urban water supply dispatching, it has experienced the traditional manual experience stage, the primary information stage of production process monitoring and data transmission. At present, we are in the artificial intelligence construction stage including SCADA system, pipe network geographic GIS system and hydraulic model system as comprehensive dispatching auxiliary means.
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References
Lu, M., Zhang, T., Zhao, H. modeling method for optimal operation of large-scale water supply system. Water Supply Drainage 27(6), 81–86 (2001)
Yimei, T., Jiangtao, L., et al.: application of genetic algorithm in optimal operation of water supply system. China Water Supply Drainage 17(12), 63–65 (2001)
Fang, Y., Hongwei, Z.: optimal operation of urban water supply network under water-saving conditions. China Water Supply Drainage 18(3), 82–84 (2002)
Zheng, D., Wang, N., Yang, J.: Optimal operation of multi-source large-scale water supply network. J. Water Conserv. 2, 1–13 (2013)
Zhiguang, N., Hongwei, Z.: Genetic algorithm for optimal operation of urban water supply system. China Water Supply Drainage 19(4), 42–44 (2003)
Shan, J., Dai, X.: Using BP network to establish a prediction model of urban water consumption. China Water Supply Drainage 17(8) (2001)
Liu, S.: Optimal distribution of water supply in pumping stations of multi-source water supply system. China Water Supply Drainage 5(4) (1988)
Zhong, W., Xu, N.: Hierarchical optimal operation of urban water supply system with booster pump station. Syst. Eng. Theory Pract. 9(5), 60–68 (1989)
Minnan, L.: hydraulic calculation and optimal operation of water supply network. J. Water Conserv. 9, 32–39 (1995)
Mackle, G., Savie, D.A., et al.: Application of genetic algorithms to pumpscheduling for water supply. In: 1995 GALESIA, First International Conference on Genetic Algorithms In Engineering Systems: Innovations and Applications, pp. 400–405
Pezeshk, S., Helweg, O.J.: Adaptive search optimization in reducing pump operating costs. J. Water Resour. Plann. Manag. ASCE 122(1), 57–63 (1996)
Niranjan Reddy, P.V., Sridharan, K., Rao, P.V.: WLS method for parameter estimation in water distribution networks. J. Water Resour. Plann. Manag. 122(3). 157–164 (1996)
Scholkopf, B., Simard, P., Smola, A.J:. Prior knowledge in support vector kernels. In: Jordan, M., Kearns, M., Solla, S. (eds.) Advance inNeural Information Processing Systems, pp. 640–646. MIT Press, Denver (1998)
Sakarya, B.A., Mays, L.W.: Optimal operation of water distribution pumps considering water quality. J. Water Resour. Plann. Manag. ASCE 126(4), 210–220 (2000)
Jowitt, P.W., Germanopoulos, G.: Optimal pump scheduling in water-supply networks. J. Water Resour. Plann. Manag. 118(4). 406-422 (1992)
Lansey, K.E., Awumah, K.: Optimal pump operation considering pump switches. J. Water Resour. Plann. Manag. 120(1), 17–35 (1994)
Ormsbee, L.E., Lansey, K.E.: Optimal control of water supply pumping systems. J. Water Resour. Plann. Manag. ASCE 120(2), 237–252 (1994)
Jain, D.A., Joshi, U.C.: Short-term water demand forecasting using artificial neural networks: IIT Kanpur experience. In: Proceedings of 15th International Conference on Pattern Recognition, vol. 2, pp. 459–462 (1994)
Acknowledgement
This work was supported by the 1st batch of Industry University Cooperative Education Projects of Ministry of Education in 2021 (202101186002 and 202101186014); the 2nd batch of Industry University Cooperative Education Projects of Ministry of Education in 2021 (202102296002); the 2021 Self-made Experimental Teaching Instrument and Equipment Project Fund of Nankai University (21NKZZYQ01); the 2022 Undergraduate Education Reform Project Fund of Nankai University and the 2022 Undergraduate Experimental Teaching Reform Project Fund of Nankai University.
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Zhang, P., Wang, H., Zhang, B., Ma, K., Xu, P. (2023). Application of Artificial Intelligence in Water Supply Dispatching of Smart City. In: Liang, Q., Wang, W., Mu, J., Liu, X., Na, Z. (eds) Artificial Intelligence in China. AIC 2022. Lecture Notes in Electrical Engineering, vol 871. Springer, Singapore. https://doi.org/10.1007/978-981-99-1256-8_7
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