Articles with public access mandates - Hongfang Lu (卢泓方)Learn more
Not available anywhere: 16
Hybrid decision tree-based machine learning models for short-term water quality prediction (Highly Cited Paper)
H Lu, X Ma
Chemosphere 249, 126169, 2020
Mandates: National Natural Science Foundation of China
Carbon trading volume and price forecasting in China using multiple machine learning models (Highly Cited Paper)
H Lu, X Ma, K Huang, M Azimi
Journal of Cleaner Production 249, 119386, 2020
Mandates: National Natural Science Foundation of China
Carbon dioxide transport via pipelines: A systematic review
H Lu, X Ma, K Huang, L Fu, M Azimi
Journal of Cleaner Production 266, 121994, 2020
Mandates: National Natural Science Foundation of China
Energy price prediction using data-driven models: A decade review
H Lu, X Ma, M Ma, S Zhu
Computer Science Review 39, 100356, 2021
Mandates: National Natural Science Foundation of China
Ultrasonic guided wave techniques and applications in pipeline defect detection: A review
X Zang, ZD Xu, H Lu, C Zhu, Z Zhang
International Journal of Pressure Vessels and Piping 206, 105033, 2023
Mandates: National Natural Science Foundation of China
US natural gas consumption prediction using an improved kernel-based nonlinear extension of the Arps decline model
H Lu, X Ma, M Azimi
Energy 194, 116905, 2020
Mandates: National Natural Science Foundation of China
Prediction of offshore wind farm power using a novel two-stage model combining kernel-based nonlinear extension of the Arps decline model with a multi-objective grey wolf optimizer
H Lu, X Ma, K Huang, M Azimi
Renewable & Sustainable Energy Reviews 127, 109856, 2020
Mandates: National Natural Science Foundation of China
Lake water-level fluctuation forecasting using machine learning models: a systematic review
S Zhu, H Lu, M Ptak, J Dai, Q Ji
Environmental Science and Pollution Research 27, 44807–44819, 2020
Mandates: National Natural Science Foundation of China
Machine learning approaches for estimation of compressive strength of concrete
M Hadzima-Nyarko, EK Nyarko, H Lu, S Zhu
European Physical Journal Plus 135, 682, 2020
Mandates: National Natural Science Foundation of China
Transformer‐optimized generation, detection, and tracking network for images with drainage pipeline defects
D Ma, H Fang, N Wang, H Lu, J Matthews, C Zhang
Computer‐Aided Civil and Infrastructure Engineering 38 (15), 2109-2127, 2023
Mandates: National Natural Science Foundation of China
Deeppipe: Theory-guided neural network method for predicting burst pressure of corroded pipelines
Y Ma, J Zheng, Y Liang, JJ Klemeš, J Du, Q Liao, H Lu, B Wang
Process Safety and Environmental Protection 162, 595-609, 2022
Mandates: National Natural Science Foundation of China, European Commission
Urban natural gas consumption forecasting by novel wavelet-kernelized grey system model
X Ma, H Lu, M Ma, L Wu, Y Cai
Engineering Applications of Artificial Intelligence 119, 105773, 2023
Mandates: National Natural Science Foundation of China
Global climate policy effectiveness: A panel data analysis
S Zheng, Y Pu, H Lu, JJ Zhang, D Wang, X Ma
Journal of Cleaner Production 412, 137321, 2023
Mandates: National Natural Science Foundation of China
Hybrid machine learning for pullback force forecasting during horizontal directional drilling
H Lu, T Iseley, J Matthews, W Liao
Automation in Construction 129, 103810, 2021
Mandates: National Natural Science Foundation of China
An Effective Data-driven Model for Predicting Energy Consumption of Long-distance Oil Pipelines
H Lu, ZD Xu, M Azimi, L Fu, Y Wang
ASCE Journal of Pipeline Systems Engineering and Practice 13 (2), 04022005, 2022
Mandates: National Natural Science Foundation of China
Predicting Solid-Particle Erosion Rate of Pipelines Using Support Vector Machine with Improved Sparrow Search Algorithm
H Peng, H Lu, ZD Xu, Y Wang, Z Zhang
ASCE Journal of Pipeline Systems Engineering and Practice 14 (2), 04022077, 2023
Mandates: National Natural Science Foundation of China
Available somewhere: 8
Short-term prediction of building energy consumption employing an improved extreme gradient boosting model: A case study of an intake tower
H Lu, F Cheng, X Ma, G Hu
Energy 203, 117756, 2020
Mandates: National Natural Science Foundation of China
A hybrid multi-objective optimizer-based model for daily electricity demand prediction considering COVID-19
H Lu, X Ma, M Ma
Energy 219, 119568, 2021
Mandates: National Natural Science Foundation of China
Impacts of the COVID-19 pandemic on the energy sector (Best Paper Award)
H Lu, X Ma, M Ma
Journal of Zhejiang University-SCIENCE A 22, 941–956, 2021
Mandates: National Natural Science Foundation of China
A hybrid machine learning model for predicting crater width formed by explosions of natural gas pipelines
G Qin, A Xia, H Lu, Y Wang, R Li, C Wang
Journal of Loss Prevention in the Process Industries 82, 104994, 2023
Mandates: National Natural Science Foundation of China
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