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Daniel Adanza Dopazo
Daniel Adanza Dopazo
Research Associate, University of West England
Verified email at uwe.ac.uk
Title
Cited by
Cited by
Year
An automatic methodology for the quality enhancement of requirements using genetic algorithms
DA Dopazo, VM Pelayo, GG Fuster
Information and Software Technology 140, 106696, 2021
162021
A Leakage Detection System with an Efficient Prioritization at a District Meter Area Level
D Adanza Dopazo, R Everson, S Rogerson, R Farmani, S Dragan
World Environmental and Water Resources Congress 2021, 1023-1032, 2021
12021
An automated machine learning approach for classifying infrastructure cost data
DA Dopazo, L Mahdjoubi, B Gething, AM Mahamadu
Computer‐Aided Civil and Infrastructure Engineering 39 (7), 1061-1076, 2024
2024
An Automated Method for Extracting and Analyzing Railway Infrastructure Cost Data
DA Dopazo, L Mahdjoubi, B Gething
Buildings 13 (10), 2405, 2023
2023
A Method to Enable Automatic Extraction of Cost and Quantity Data from Hierarchical Construction Information Documents to Enable Rapid Digital Comparison and Analysis
DA Dopazo, L Mahdjoubi, B Gething
Preprints, 2023
2023
World Environmental and Water Resources Congress 2021
LA Baldwin, PEVG Gude
2021
STROJNO UČENJE NA VELIKIH PODATKIH Z UPORABO MONGODB, R IN HADOOP
D Adanza Dopazo
Univerza v Mariboru, Fakulteta za elektrotehniko, računalništvo in informatiko, 2016
2016
A methodology based on machine learning and data science for assessing the movement quality.
DA Dopazo, M Al-amri, K Button, S Gardner, J Kinsey-Jones
A leakage detection system extracting the most meaningful features with decision trees.
DA Dopazo
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Articles 1–9