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Dr. Manish Kumar
Dr. Manish Kumar
SRMIST, Trichy, Assistant professor
Zweryfikowany adres z srmist.edu.in
Tytuł
Cytowane przez
Cytowane przez
Rok
Reliability analysis of pile foundation using ELM and MARS
M Kumar, P Samui
Geotechnical and geological engineering 37, 3447-3457, 2019
552019
Reliability analysis of pile foundation using soft computing techniques: a comparative study
M Kumar, A Bardhan, P Samui, JW Hu, MR Kaloop
Processes 9 (3), 486, 2021
482021
Reliability analysis of settlement of pile group in clay using LSSVM, GMDH, GPR
M Kumar, P Samui
Geotechnical and Geological Engineering 38 (6), 6717-6730, 2020
442020
State of art soft computing based simulation models for bearing capacity of pile foundation: a comparative study of hybrid ANNs and conventional models
M Kumar, V Kumar, BG Rajagopal, P Samui, A Burman
Modeling Earth Systems and Environment 9 (2), 2533-2551, 2023
312023
A novel integrated approach of RUNge Kutta optimizer and ANN for estimating compressive strength of self-compacting concrete
R Biswas, M Kumar, RK Singh, M Alzara, SBA El Sayed, M Abdelmongy, ...
Case Studies in Construction Materials 18, e02163, 2023
292023
Soft computing-based prediction models for compressive strength of concrete
M Kumar, R Biswas, DR Kumar, P Samui, MR Kaloop, M Eldessouki
Case Studies in Construction Materials 19, e02321, 2023
282023
Optimized neural network-based state-of-the-art soft computing models for the bearing capacity of strip footings subjected to inclined loading
DR Kumar, W Wipulanusat, M Kumar, S Keawsawasvong, P Samui
Intelligent Systems with Applications 21, 200314, 2024
272024
Metaheuristic models for the prediction of bearing capacity of pile foundation
M Kumar, R Biswas, DR Kumar, P Samui
Geomechanics and Engineering 31 (2), 129-147, 2022
272022
Hybrid ELM and MARS-based prediction model for bearing capacity of shallow foundation
M Kumar, V Kumar, R Biswas, P Samui, MR Kaloop, M Alzara, AM Yosri
Processes 10 (5), 1013, 2022
262022
Reliability analysis of settlement of pile group
M Kumar, P Samui, D Kumar, W Zhang
Innovative Infrastructure Solutions 6, 1-17, 2021
262021
Reliability analysis of pile foundation using GMDH, GP and MARS
M Kumar, P Samui
CIGOS 2021, Emerging Technologies and Applications for Green Infrastructure …, 2022
232022
Prediction of bearing capacity of pile foundation using deep learning approaches
M Kumar, DR Kumar, J Khatti, P Samui, KS Grover
Frontiers of Structural and Civil Engineering 18 (6), 870-886, 2024
222024
State-of-the-art XGBoost, RF and DNN based soft-computing models for PGPN piles
M Kumar, P Samui, DR Kumar, PG Asteris
Geomechanics and Geoengineering 19 (6), 975-990, 2024
162024
Genetic programming based compressive strength prediction model for green concrete
M Kumar, DS TN
Materials Today: Proceedings, 2023
142023
A novel approach to estimate rock deformation under uniaxial compression using a machine learning technique
DR kumar, M Kumar, P Samui, DJ Armaghani
Bulletin of Engineering Geology and the Environment 83 (7), 278, 2024
92024
A novel XGBoost and RF-based metaheuristic models for concrete compression strength
M Kumar, NZ Fathima, DR Kumar
International Conference on Civil Engineering Innovative Development in …, 2023
92023
A hybrid Cycle GAN-based lightweight road perception pipeline for road dataset generation for Urban mobility
BG Rajagopal, M Kumar, AH Alshehri, F Alanazi, AF Deifalla, AM Yosri, ...
Plos one 18 (11), e0293978, 2023
82023
Influence of variation of soil properties in bearing capacity and settlement analysis of a strip footing using random finite element method
V Kumar, A Burman, FHM Portelinha, M Kumar, G Das
Civil Engineering Infrastructures Journal 57 (2), 383-403, 2024
52024
Application of novel deep neural network on prediction of compressive strength of fly ash based concrete
R Biswas, M Kumar, DR Kumar, P Samui, MK Rajak, DJ Armaghani, ...
Nondestructive Testing and Evaluation, 1-31, 2024
52024
Reliability-based design for strip-footing subjected to inclined loading using hybrid LSSVM ML models
M Kumar, DR Kumar, W Wipulanusat
Geotechnical and Geological Engineering 42 (8), 7677-7697, 2024
52024
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