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Liquefaction behavior of Indo-Gangetic region using novel metaheuristic optimization algorithms coupled with artificial neural network

Natural hazards (Dordrecht), 2022-04, Vol.111 (3), p.2995-3029

2022

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Reliability Analysis for Liquefaction Risk Assessment for the City of Patna, India using Hybrid Computational Modeling

Journal of the Geological Society of India, 2022-10, Vol.98 (10), p.1395-1406

2022

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A novel liquefaction study for fine-grained soil using PCA-based hybrid soft computing models

Sadhana (Bangalore), 2021-09, Vol.46 (3), Article 113

2021

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Insight into the Effect of Fine Content on Liquefaction Behavior of Soil

Geotechnical and geological engineering, 2021, Vol.39 (1), p.1-12

2021

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Prediction of the Seismic Effect on Liquefaction Behavior of Fine-Grained Soils Using Artificial Intelligence-Based Hybridized Modeling

Arabian journal for science and engineering (2011), 2022-04, Vol.47 (4), p.5411-5441

2022

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Prediction of Liquefaction Behaviour of Fine-Grained Soil Using Nature-Inspired Optimized Algorithms Coupled with Neural Network

Indian Geotechnical Journal, 2024-10, Vol.54 (5), p.1941-1959

2024

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Geocell Mattress Reinforcement for Bottom Ash: A Comprehensive Study of Load-Settlement Characteristics

Iranian journal of science and technology. Transactions of civil engineering, 2024-04, Vol.48 (2), p.727-743

2024

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Probabilistic Study of Liquefaction Response of Fine-Grained Soil Using Multi-Linear Regression Model

Journal of the Institution of Engineers (India). Series A, Civil, architectural, environmental and agricultural Engineering, 2021-09, Vol.102 (3), p.783-803

2021

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Modelling Soil Compaction Parameters Using an Enhanced Hybrid Intelligence Paradigm of ANFIS and Improved Grey Wolf Optimiser

Mathematics (Basel), 2023-07, Vol.11 (14), p.3064

2023

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Comparative and parametric study of AI-based models for risk assessment against soil liquefaction for high-intensity earthquakes

Arabian journal of geosciences, 2022-07, Vol.15 (14), Article 1262

2022

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Prediction of soil liquefaction for railway embankment resting on fine soil deposits using enhanced machine learning techniques

Journal of Earth System Science, 2023-09, Vol.132 (3), p.145, Article 145

2023

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Experimental and Reliability Study of Nano-Silica Stabilized Problematic Soil in Lesser Himalayan Region

Geotechnical and geological engineering, 2024-10

2024

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Advancing earth science in geotechnical engineering: A data-driven soft computing technique for unconfined compressive strength prediction in soft soil

Journal of Earth System Science, 2024-08, Vol.133 (3), p.159

2024

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Estimation of California bearing ratio for hill highways using advanced hybrid artificial neural network algorithms

Multiscale and Multidisciplinary Modeling, Experiments and Design, 2024-06, Vol.7 (2), p.1119-1144

2024

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Applying Optimized Machine Learning Models for Predicting Unconfined Compressive Strength in Fine-Grained Soil

Transportation infrastructure geotechnology, 2024-08, Vol.11 (4), p.2235-2269

2024

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Enhancing unconfined compressive strength prediction in nano-silica stabilized soil: a comparative analysis of ensemble and deep learning models

Modeling earth systems and environment, 2024-08, Vol.10 (4), p.5079-5102

2024

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Liquefaction study of fine-grained soil using computational model

Innovative infrastructure solutions : the official journal of the Soil-Structure Interaction Group in Egypt (SSIGE), 2021-06, Vol.6 (2), Article 58

2021

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Enhancing predictive accuracy: a comprehensive study of optimized machine learning models for ultimate load-carrying capacity prediction in SCFST columns

Asian journal of civil engineering. Building and housing, 2024-06, Vol.25 (4), p.3081-3098

2024

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Evaluating seismic resilience of steel buildings: integrating soil-structure interaction and ensemble modeling approaches

Modeling earth systems and environment, 2024-09

2024

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Modelling and validation of liquefaction potential index of fine-grained soils using ensemble learning paradigms

Soil dynamics and earthquake engineering (1984), 2024-02, Vol.177, p.108399, Article 108399

2024

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Applications of bentonite in plastic concrete: a comprehensive study on enhancing workability and predicting compressive strength using hybridized AI models

Asian journal of civil engineering. Building and housing, 2024-06, Vol.25 (4), p.3113-3128

2024

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Enhancing seismic vulnerability assessment: a neural network effort for efficient prediction of multi-storey reinforced concrete building displacement

Asian journal of civil engineering. Building and housing, 2024-04, Vol.25 (3), p.2843-2865

2024

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Data-driven machine learning approaches for predicting permeability and corrosion risk in hybrid concrete incorporating blast furnace slag and fly ash

Asian journal of civil engineering. Building and housing, 2024-06, Vol.25 (4), p.3263-3275

2024

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Prediction of California Bearing Ratio of nano-silica and bio-char stabilized soft sub-grade soils using explainable machine learning

Transportation Geotechnics, 2024-11, Vol.49, p.101387, Article 101387

2024

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Machine learning approaches for real-time prediction of compressive strength in self-compacting concrete

Asian journal of civil engineering. Building and housing, 2024-04, Vol.25 (3), p.2743-2760

2024

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Liquefaction behavior of Indo-Gangetic region using novel metaheuristic optimization algorithms coupled with artificial neural network

Reliability Analysis for Liquefaction Risk Assessment for the City of Patna, India using Hybrid Computational Modeling

A novel liquefaction study for fine-grained soil using PCA-based hybrid soft computing models

Insight into the Effect of Fine Content on Liquefaction Behavior of Soil

Prediction of the Seismic Effect on Liquefaction Behavior of Fine-Grained Soils Using Artificial Intelligence-Based Hybridized Modeling

Prediction of Liquefaction Behaviour of Fine-Grained Soil Using Nature-Inspired Optimized Algorithms Coupled with Neural Network

Geocell Mattress Reinforcement for Bottom Ash: A Comprehensive Study of Load-Settlement Characteristics

Probabilistic Study of Liquefaction Response of Fine-Grained Soil Using Multi-Linear Regression Model

Modelling Soil Compaction Parameters Using an Enhanced Hybrid Intelligence Paradigm of ANFIS and Improved Grey Wolf Optimiser

Comparative and parametric study of AI-based models for risk assessment against soil liquefaction for high-intensity earthquakes

Prediction of soil liquefaction for railway embankment resting on fine soil deposits using enhanced machine learning techniques

Experimental and Reliability Study of Nano-Silica Stabilized Problematic Soil in Lesser Himalayan Region

Advancing earth science in geotechnical engineering: A data-driven soft computing technique for unconfined compressive strength prediction in soft soil

Estimation of California bearing ratio for hill highways using advanced hybrid artificial neural network algorithms

Applying Optimized Machine Learning Models for Predicting Unconfined Compressive Strength in Fine-Grained Soil

Enhancing unconfined compressive strength prediction in nano-silica stabilized soil: a comparative analysis of ensemble and deep learning models

Liquefaction study of fine-grained soil using computational model

Enhancing predictive accuracy: a comprehensive study of optimized machine learning models for ultimate load-carrying capacity prediction in SCFST columns

Evaluating seismic resilience of steel buildings: integrating soil-structure interaction and ensemble modeling approaches

Modelling and validation of liquefaction potential index of fine-grained soils using ensemble learning paradigms

Applications of bentonite in plastic concrete: a comprehensive study on enhancing workability and predicting compressive strength using hybridized AI models

Enhancing seismic vulnerability assessment: a neural network effort for efficient prediction of multi-storey reinforced concrete building displacement

Data-driven machine learning approaches for predicting permeability and corrosion risk in hybrid concrete incorporating blast furnace slag and fly ash

Prediction of California Bearing Ratio of nano-silica and bio-char stabilized soft sub-grade soils using explainable machine learning

Machine learning approaches for real-time prediction of compressive strength in self-compacting concrete

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