000			01695nam a22001337a 4500
008			250822b |||||||| |||| 00| 0 eng d
100			_aSuja S. Nair
245			_aPrediction of Reliability for Water Distribution System Using ANN and Benchmark Table
300			_ap649–664
520			_aThis study employs artificial neural networks (ANN) and benchmark tables to forecast the water distribution system reliability in the Panchayats of Elamkunnapuzha, Njarakkal, and Nayarambalam (Zone IIB) in Cochin, Kerala. The research uses water usage data collected from 90 Kerala Water Authority (KWA) customers over 7 months (December 2022 to June 2023). A questionnaire-based survey was conducted with these customers to gather insights on the network's performance, validating the accuracy of the predictions generated by the ANN model. The study identifies several factors impacting the performance of the water distribution network, including system capacity, seasonal fluctuations, and customer usage patterns. The ANN model is employed to predict water demand from 2024 to 2034, assessing the reliability of the gridiron network in meeting future demands. The results of this study provide valuable insights into the functionality of the current network and highlight necessary adjustments to ensure continued reliability in the face of growing water demand in the region.
654			_aBuilding Information Modeling _aChemical Process Reliability _aDrought _aSmart Infrastructure _aWater Industry and Water Technology _aWater Policy
773	0		_080299 _9113445 _dGermany Springer Nature India Private limited _tJournal of the Institution of engineers (India): series A _x2250-2149
942			_cJA
999			_c132533 _d132533