Inundation risk assessment of metro system using AHP and TFN-AHP in Shenzhen

Sustainable Cities and Society, Journal Year: 2020, Volume and Issue: 56, P. 102103 - 102103

Published: Feb. 19, 2020

Language: Английский

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Improved prediction of slope stability using a hybrid stacking ensemble method based on finite element analysis and field data

Journal of Rock Mechanics and Geotechnical Engineering, Journal Year: 2020, Volume and Issue: 13(1), P. 188 - 201

Published: Nov. 23, 2020

Slope failures lead to catastrophic consequences in numerous countries and thus the stability assessment for slopes is of high interest geotechnical geological engineering researches. A hybrid stacking ensemble approach proposed this study enhancing prediction slope stability. In approach, we used an artificial bee colony (ABC) algorithm find out best combination base classifiers (level 0) determined a suitable meta-classifier 1) from pool 11 individual optimized machine learning (OML) algorithms. Finite element analysis (FEA) was conducted order form synthetic database training stage (150 cases) model while 107 real field cases were testing stage. The results by then compared with that obtained OML methods using confusion matrix, F1-score, area under curve, i.e. AUC-score. comparisons showed significant improvement ability has been achieved (AUC = 90.4%), which 7% higher than 82.9%). Then, further comparison undertaken between method basic classifier on prediction. prominent performance over method. Finally, importance variables studied linear vector quantization (LVQ)

Language: Английский

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Risk assessment and management of excavation system based on fuzzy set theory and machine learning methods

Automation in Construction, Journal Year: 2020, Volume and Issue: 122, P. 103490 - 103490

Published: Dec. 28, 2020

Language: Английский

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Prediction of Disc Cutter Life During Shield Tunneling with AI via the Incorporation of a Genetic Algorithm into a GMDH-Type Neural Network

Engineering, Journal Year: 2020, Volume and Issue: 7(2), P. 238 - 251

Published: Sept. 2, 2020

Disc cutter consumption is a critical problem that influences work performance during shield tunneling processes and directly affects the change decision. This study proposes new model to estimate disc life (Hf) by integrating group method of data handling (GMDH)-type neural network (NN) with genetic algorithm (GA). The efficiency effectiveness GMDH structure are optimized GA, which enables each neuron search for its optimum connections set from previous layer. With proposed model, monitoring including database, consumption, geological conditions, operational parameters can be analyzed. To verify case in China presented database adopted illustrate excellence hybrid model. results indicate predicts high accuracy. sensitivity analysis reveals penetration rate (PR) has significant influence on life. this beneficial both planning construction stages tunneling.

Language: Английский

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State-of-the-Art Review of Machine Learning Applications in Constitutive Modeling of Soils

Archives of Computational Methods in Engineering, Journal Year: 2021, Volume and Issue: 28(5), P. 3661 - 3686

Published: Jan. 5, 2021

Language: Английский

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Prevention/mitigation of natural disasters in urban areas

Smart Construction and Sustainable Cities, Journal Year: 2023, Volume and Issue: 1(1)

Published: Aug. 9, 2023

Abstract Preventing/mitigating natural disasters in urban areas can indirectly be part of the 17 sustainable economic and social development intentions according to United Nations 2015. Four types disasters—flooding, heavy rain-induced slope failures/landslides; earthquakes causing structure failure/collapse, land subsidence—are briefly considered this article. With increased frequency climate change-induced extreme weathers, numbers flooding failures/landslides has recent years. There are both engineering methods prevent their occurrence, more effectively early prediction warning systems mitigate resulting damage. However, still cannot predicted an extent that is sufficient avoid damage, developing adopting structures resilient against earthquakes, is, featuring earthquake resistance, vibration damping, seismic isolation, essential tasks for city development. Land subsidence results from human activity, mainly due excessive pumping groundwater, which a “natural” disaster caused by activity. Countermeasures include effective regional and/or national freshwater management local water recycling groundwater. Finally, perspectives risk hazard prevention through enhanced field monitoring, assessment with multi-criteria decision-making (MCDM), artificial intelligence (AI) technology.

Language: Английский

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Dynamic prediction of jet grouted column diameter in soft soil using Bi-LSTM deep learning

Acta Geotechnica, Journal Year: 2020, Volume and Issue: 16(1), P. 303 - 315

Published: July 2, 2020

Language: Английский

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Groundwater Estimation from Major Physical Hydrology Components Using Artificial Neural Networks and Deep Learning

Water, Journal Year: 2019, Volume and Issue: 12(1), P. 5 - 5

Published: Dec. 18, 2019

Precise estimation of physical hydrology components including groundwater levels (GWLs) is a challenging task, especially in relatively non-contiguous watersheds. This study estimates GWLs with deep learning and artificial neural networks (ANNs), namely multilayer perceptron (MLP), long short term memory (LSTM), convolutional network (CNN) four different input variable combinations for two watersheds (Baltic River Long Creek) Prince Edward Island, Canada. Variables stream level, flow, precipitation, relative humidity, mean temperature, evapotranspiration, heat degree days, dew point evapotranspiration the 2011–2017 period were used as variables. Using hit trial approach various hyperparameters, all ANNs trained from scratched (2011–2015) validated (2016–2017). The level was major contributor to GWL fluctuation Baltic Creek (R2 = 50.8 49.1%, respectively). MLP performed better validation (RMSE 0.471 1.15, Increased number variables 1 4 improved RMSE watershed by 11% 1.6%. techniques introduced this estimate fluctuations are convenient accurate compared collection periodic dips based on monitoring wells inventory control management.

Language: Английский

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Application of LSTM approach for modelling stress–strain behaviour of soil

Applied Soft Computing, Journal Year: 2020, Volume and Issue: 100, P. 106959 - 106959

Published: Dec. 1, 2020

Language: Английский

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Analyses of leakage effect of waterproof curtain during excavation dewatering

Journal of Hydrology, Journal Year: 2020, Volume and Issue: 583, P. 124582 - 124582

Published: Jan. 18, 2020

Language: Английский

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