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Nursulu Kuzhagaliyeva
Nursulu Kuzhagaliyeva
Energy modelling, Technology Innovation Institute
Verified email at kaust.edu.sa
Title
Cited by
Cited by
Year
Using deep neural networks to diagnose engine pre-ignition
N Kuzhagaliyeva, A Thabet, E Singh, B Ghanem, SM Sarathy
Proceedings of the Combustion Institute 38 (4), 5915-5922, 2021
132021
Artificial intelligence-driven design of fuel mixtures
N Kuzhagaliyeva, S Horváth, J Williams, A Nicolle, SM Sarathy
Communications Chemistry 5 (1), 111, 2022
102022
Using deep learning to diagnose preignition in turbocharged spark-ignited engines
E Singh, N Kuzhagaliyeva, SM Sarathy
Artificial Intelligence and Data Driven Optimization of Internal Combustion …, 2022
102022
Uncertainty quantification of a deep learning fuel property prediction model
KK Yalamanchi, S Kommalapati, P Pal, N Kuzhagaliyeva, AS AlRamadan, ...
Applications in Energy and Combustion Science 16, 100211, 2023
22023
Mixtures Recomposition by Neural Nets: A Multidisciplinary Overview
A Nicolle, S Deng, M Ihme, N Kuzhagaliyeva, EA Ibrahim, A Farooq
Journal of Chemical Information and Modeling, 2024
12024
Predicting Vehicle Engine Performance: Assessment of Machine Learning Techniques and Data Imputation
JCG Delgado, N Kuzhagaliyeva, I Gorbatenko, M Sarathy
SAE Technical Paper, 2024
2024
Artificial-intelligence driven design of liquid fuels.
N Kuzhagaliyeva
2024
Uncertainty Quantification of a Deep Learning Based Fuel Property Prediction Model
S Kommalapati, P Pal, N Kuzhagaliyeva, A AlRamadan, B Mohan, Y Pei, ...
Bulletin of the American Physical Society 67, 2022
2022
Detection of Pre-ignition Events using Deep Neural Networks
N Kuzhagaliyeva
2019
Size and purity controlled synthesis of silver nanoparticles for mercury (II) ion extraction from aqueous solutions
K Amangeldiuly, NA Kuzhagaliyeva, AV Korobeinyk, RLD Whitby
8th International Conference on Nanomaterials-Research and Application …, 2016
2016
Applications in Energy and Combustion Science
KK Yalamanchi, S Kommalapati, P Pal, N Kuzhagaliyeva, AS AlRamadan, ...
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