An improved failure mode and effect analysis method for group decision-making in utility tunnels construction project risk evaluation

Reliability Engineering & System Safety, Год журнала: 2024, Номер 244, С. 109943 - 109943

Опубликована: Янв. 11, 2024

Язык: Английский

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An integrated framework for the comprehensive evaluation of low impact development strategies

Journal of Environmental Management, Год журнала: 2021, Номер 294, С. 113023 - 113023

Опубликована: Июнь 10, 2021

Язык: Английский

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GIS-based multi-criteria analysis for flood prone areas mapping in the trans-boundary Shatt Al-Arab basin, Iraq-Iran

Geomatics Natural Hazards and Risk, Год журнала: 2021, Номер 12(1), С. 2087 - 2116

Опубликована: Янв. 1, 2021

Severe flood events in the trans-boundary Shatt Al-Arab basin (Iraq-Iran) claim hundreds of human lives and cause damage to economy environment. Therefore, developing a hazard model recognize basin's susceptible areas flooding is important for decision makers comprehensive risk management. The map was prepared using geographical information systems (GIS) multi-criteria analysis (MCDA) along with application analytical hierarchy process (AHP) method identify optimal selection weights factors that contribute risk. causative used this study were rainfall, distance river, digital elevation (DEM), slope, land use/land cover (LULC), drainage density, soils, lithology. derived consisted four distinct categories (zones). These zones depict high, intermediate, low, very low around 20%, 40%, 39%, 2% area, respectively. produced further verified historical event area. results found be consistent data events, revealing model's effectiveness realistic representation mapping.

Язык: Английский

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Modelling the performance of EPB shield tunnelling using machine and deep learning algorithms

Geoscience Frontiers, Год журнала: 2021, Номер 12(5), С. 101177 - 101177

Опубликована: Фев. 23, 2021

This paper introduces an intelligent framework for predicting the advancing speed during earth pressure balance (EPB) shield tunnelling. Five artificial intelligence (AI) models based on machine and deep learning techniques—back-propagation neural network (BPNN), extreme (ELM), support vector (SVM), long-short term memory (LSTM), gated recurrent unit (GRU)—are used. geological nine operational parameters that influence are considered. A field case of tunnelling in Shenzhen City, China is analyzed using developed models. total 1000 datasets adopted to establish The prediction performance five ranked as GRU > LSTM SVM ELM BPNN. Moreover, Pearson correlation coefficient (PCC) sensitivity analysis. results reveal main thrust (MT), penetration (P), foam volume (FV), grouting (GV) have strong correlations with (AS). An empirical formula constructed high-correlation influential factors their corresponding datasets. Finally, performances method compared. all perform better than method.

Язык: Английский

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Real-time prediction of shield moving trajectory during tunnelling using GRU deep neural network

Acta Geotechnica, Год журнала: 2021, Номер 17(4), С. 1167 - 1182

Опубликована: Июль 30, 2021

Язык: Английский

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Time-series prediction of shield movement performance during tunneling based on hybrid model

Tunnelling and Underground Space Technology, Год журнала: 2021, Номер 119, С. 104245 - 104245

Опубликована: Окт. 28, 2021

Язык: Английский

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A cloud model-based approach for risk analysis of excavation system

Reliability Engineering & System Safety, Год журнала: 2022, Номер 231, С. 108984 - 108984

Опубликована: Ноя. 16, 2022

Язык: Английский

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Dynamic risk analysis of accidents chain and system protection strategy based on complex network and node structure importance

Reliability Engineering & System Safety, Год журнала: 2023, Номер 238, С. 109413 - 109413

Опубликована: Июнь 3, 2023

Язык: Английский

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Applying an entropy-weighted TOPSIS method to evaluate energy green consumption revolution progressing of China

Environmental Science and Pollution Research, Год журнала: 2023, Номер 30(14), С. 42267 - 42281

Опубликована: Янв. 16, 2023

Язык: Английский

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New threshold for landslide warning in the southern part of Thailand integrates cumulative rainfall with event rainfall depth-duration

Natural Hazards, Год журнала: 2022, Номер 113(1), С. 125 - 141

Опубликована: Март 10, 2022

Язык: Английский

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