Abstract
As interest in the development of artificial intelligence technology in the water supply field increases, an artificial neural network algorithm that can predict improved decision ratings through repetitive learning using results of aging pipe condition evaluation data should be developed and the most reliable prediction model should be presented through a verification process. An algorithm was developed to predict pipeline ratings by updating weights through backpropagation so that 12 items of indirect evaluation data according to the 2020 Han River Basin
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