首页|University of Port Harcourt Researcher Reports Recent Findings in Machine Learning (Development of a Fault Detection and Localization Model for a Water Distribution Network)
University of Port Harcourt Researcher Reports Recent Findings in Machine Learning (Development of a Fault Detection and Localization Model for a Water Distribution Network)
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New research on artificial intelligence is the subject of a new report. According to news originating from Port Harcourt, Nigeria, by NewsRx editors, the research stated, "Water distribution networks are complex systems that aid in the delivery of water to residential and non-residential areas." Our news journalists obtained a quote from the research from University of Port Harcourt: "However, the networks can be affected by different types of faults, which could lead to the wastage of treated water. As such, there is a need to develop a reliable leakage detection and localization system that can detect leak occurrences in the network. This study, using a simulated dataset from EPANET, presents the application of supervised machine learning classifiers for leak detection and localization in the water distribution network of the University of Port Harcourt Choba campus. The study compared three machine learning classification tools that are used in pattern recognition analysis: the support vector machine, knearest neighbor, and artificial neural network. The robustness and effectiveness of the proposed approach are compared with those of the performance of the classifiers for leakage detection in the network of the case study. The results show that the support vector machine performs the best, with 79% accuracy, while the respective accuracies for the remaining classifiers are 70% for the k-nearest neighbor and 61% for the artificial neural networks."
University of Port HarcourtPort HarcourtNigeriaAfricaCyborgsEmerging TechnologiesK-nearest NeighborMachine LearningSupport Vector MachinesVector Machines
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