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@article{ART002891731},
author={Gi-Tae Kim and Min, Byung-Won and Yong sun Oh},
title={Model Analysis of AI-Based Water Pipeline Improved Decision},
journal={Journal of Internet of Things and Convergence},
issn={2466-0078},
year={2022},
volume={8},
number={5},
pages={11-16},
doi={10.20465/KIOTS.2022.8.5.011}

TY - JOUR
AU - Gi-Tae Kim
AU - Min, Byung-Won
AU - Yong sun Oh
TI - Model Analysis of AI-Based Water Pipeline Improved Decision
JO - Journal of Internet of Things and Convergence
PY - 2022
VL - 8
IS - 5
PB - The Korea Internet of Things Society
SP - 11
EP - 16
SN - 2466-0078
AB - As an interest in the development of artificial intelligence(AI) technology in the water supply sector increases, we have developed an AI algorithm that can predict improvement decision-making ratings through repetitive learning using the data of pipe condition evaluation results, and present the most reliable prediction model through a verification process. We have developed the algorithm that can predict pipe ratings by pre-processing 12 indirect evaluation items based on the 2020 Han River Basin's basic plan and applying the AI algorithm to update weighting factors through backpropagation. This method ensured that the concordance rate between the direct evaluation result value and the calculated result value through repetitive learning and verification was more than 90%. As a result of the algorithm accuracy verification process, it was confirmed that all water pipe type data were evenly distributed, and the more learning data, the higher prediction accuracy. If data from all across the country is collected, the reliability of the prediction technique for pipe ratings using AI algorithm will be improved, and therefore, it is expected that the AI algorithm will play a role in supporting decision-making in the objective evaluation of the condition of aging pipes.
KW - Artificial Intelligence Technology;Data Analysis;Aging Pipe Condition Evaluation;Algorithm Model;Indirect Evaluation;Direct Evaluation
DO - 10.20465/KIOTS.2022.8.5.011
ER -

Gi-Tae Kim, Min, Byung-Won and Yong sun Oh. (2022). Model Analysis of AI-Based Water Pipeline Improved Decision. Journal of Internet of Things and Convergence, 8(5), 11-16.

Gi-Tae Kim, Min, Byung-Won and Yong sun Oh. 2022, "Model Analysis of AI-Based Water Pipeline Improved Decision", Journal of Internet of Things and Convergence, vol.8, no.5 pp.11-16. Available from: doi:10.20465/KIOTS.2022.8.5.011

Gi-Tae Kim, Min, Byung-Won, Yong sun Oh "Model Analysis of AI-Based Water Pipeline Improved Decision" Journal of Internet of Things and Convergence 8.5 pp.11-16 (2022) : 11.

Gi-Tae Kim, Min, Byung-Won, Yong sun Oh. Model Analysis of AI-Based Water Pipeline Improved Decision. 2022; 8(5), 11-16. Available from: doi:10.20465/KIOTS.2022.8.5.011

Gi-Tae Kim, Min, Byung-Won and Yong sun Oh. "Model Analysis of AI-Based Water Pipeline Improved Decision" Journal of Internet of Things and Convergence 8, no.5 (2022) : 11-16.doi: 10.20465/KIOTS.2022.8.5.011

Gi-Tae Kim; Min, Byung-Won; Yong sun Oh. Model Analysis of AI-Based Water Pipeline Improved Decision. Journal of Internet of Things and Convergence, 8(5), 11-16. doi: 10.20465/KIOTS.2022.8.5.011

Gi-Tae Kim; Min, Byung-Won; Yong sun Oh. Model Analysis of AI-Based Water Pipeline Improved Decision. Journal of Internet of Things and Convergence. 2022; 8(5) 11-16. doi: 10.20465/KIOTS.2022.8.5.011

Gi-Tae Kim, Min, Byung-Won, Yong sun Oh. Model Analysis of AI-Based Water Pipeline Improved Decision. 2022; 8(5), 11-16. Available from: doi:10.20465/KIOTS.2022.8.5.011

Gi-Tae Kim, Min, Byung-Won and Yong sun Oh. "Model Analysis of AI-Based Water Pipeline Improved Decision" Journal of Internet of Things and Convergence 8, no.5 (2022) : 11-16.doi: 10.20465/KIOTS.2022.8.5.011