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Neal Barton
Neal Barton
Unknown affiliation
Verified email at cranfield.ac.uk
Title
Cited by
Cited by
Year
Improving pipe failure predictions: Factors affecting pipe failure in drinking water networks
NA Barton, TS Farewell, SH Hallett, TF Acland
Water research 164, 114926, 2019
1642019
Using generalized additive models to investigate the environmental effects on pipe failure in clean water networks
NA Barton, TS Farewell, SH Hallett
Npj Clean Water 3 (1), 31, 2020
342020
The challenges of predicting pipe failures in clean water networks: a view from current practice
NA Barton, SH Hallett, SR Jude
Water Supply 22 (1), 527-541, 2022
202022
An evolution of statistical pipe failure models for drinking water networks: a targeted review
NA Barton, SH Hallett, SR Jude, TH Tran
Water Supply 22 (4), 3784-3813, 2022
172022
Predicting the risk of pipe failure using gradient boosted decision trees and weighted risk analysis
NA Barton, SH Hallett, SR Jude, TH Tran
NPJ Clean Water 5 (1), 22, 2022
92022
Using generalized additive models to investigate the environmental effects on pipe failure in clean water networks.” npj Clean Water 3 (1): 31
NA Barton, TS Farewell, SH Hallett
62020
文献抄録 管路破損予測モデルの精度向上: 配水管網における管路破損に影響を及ぼす要因: NA Barton, TS Farewell, SH Hallett and TF Acland," Improving pipe failure predictions: Factors …
NA Barton, TS Farewell, SH Hallett, TF Acland
水道協会雑誌= Journal of Japan Water Works Association 92 (4), 54-56, 2023
2023
corrected Proof
NA Barton, SH Hallett, SR Jude, TH Tran
2021
Proactively managing drinking water distribution networks: A data-driven, statistical modelling approach to predict the risk of pipe failure.
NA Barton
Cranfield University, 0
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Articles 1–9