Akhil Garg

47 papers C 2Journal 37Unranked 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
Assessment of free vibration frequencies of nano-scale functionally graded materials using hybrid machine learning approaches.
Neurocomputing
Mohamed-Ouejdi Belarbi, Abdelhak Khechai, Abdelfodhil Bouhdjar, Pham Van Vinh, Aman Garg, Li Li, Akhil Garg
2025 J jnl
Multidisciplinary robust design optimization under combined parameter and surrogate model uncertainties: a new computational framework for sparse samples and extreme scenarios.
Eng. Comput.
Wei Li, Yuzhen Niu, Yunhan He, Akhil Garg, Haihong Huang, Liang Gao
2024 — conf
Battery Health Prediction Using Commixtured Multi-Feature Selection and Transfer Learning.
ISGT Asia
Nitika Ghosh, Akhil Garg, Alexander Warnecke
2024 J jnl
Risk-Based Design Optimization via Scenario Generation and Genetic Programming Under Hybrid Uncertainties.
J. Comput. Inf. Sci. Eng.
Wei Li, Xiaowei Zhou, Haihong Huang, Akhil Garg, Liang Gao
2024 J jnl
Tropical modeling of battery swapping and charging station.
CoRR
Nikolai K. Krivulin, Akhil Garg
2023 J jnl
A Machine Learning Approach for Energy-Efficient Intelligent Transportation Scheduling Problem in a Real-World Dynamic Circumstances.
IEEE Trans. Intell. Transp. Syst.
Jianhui Mou, Kaizhou Gao, Peiyong Duan, Junqing Li, Akhil Garg, Rohit Sharma
2023 J jnl
An Evolving Quantum Fuzzy Neural Network for online State-of-Health estimation of Li-ion cell.
Appl. Soft Comput.
Nitika Ghosh, Akhil Garg, Bijaya K. Panigrahi, Jonghoon Kim
2023 J jnl
Surrogate-assisted multi-objective evolutionary optimization with a multi-offspring method and two infill criteria.
Swarm Evol. Comput.
Fan Li, Liang Gao, Weiming Shen, Akhil Garg
2022 J jnl
A Genetic Algorithm and RNN-LSTM Model for Remaining Battery Capacity Prediction.
J. Comput. Inf. Sci. Eng.
Mukul Singh, Shrey Bansal, Vandana, Bijaya K. Panigrahi, Akhil Garg
2022 — conf
Conceptualizing A Battery Swapping Station: A Case Study in Malaysia.
IICAIET
Elvin Cheah Ee Sheng, Christina Chin May May, Novita Sakundarini, Akhil Garg
2022 J jnl
Multidisciplinary robust design optimization considering parameter and metamodeling uncertainties.
Eng. Comput.
Wei Li, Liang Gao, Akhil Garg, Mi Xiao
2022 C conf
State of Health Estimation of Lithium-Ion Batteries for Dynamic Driving Profiles Based on Feature Extraction from Battery Relaxation Time Using Machine Learning.
IECON
Nitika Ghosh, Akhil Garg, Alexander Warnecke, Bijaya K. Panigrahi
2021 J jnl
A New Approach to Solve Uncertain Multidisciplinary Design Optimization Based on Conditional Value at Risk.
IEEE Trans Autom. Sci. Eng.
Wei Li, Mi Xiao, Akhil Garg, Liang Gao
2021 J jnl
A comparative study of pre-screening strategies within a surrogate-assisted multi-objective algorithm framework for computationally expensive problems.
Neural Comput. Appl.
Fan Li, Liang Gao, Akhil Garg, Weiming Shen, Shifeng Huang
2021 J jnl
Hybrid Strategy of Multiple Optimization Algorithms Applied to 3-D Terrain Node Coverage of Wireless Sensor Network.
Wirel. Commun. Mob. Comput.
Li-Gang Zhang, Fang Fan, Shu-Chuan Chu, Akhil Garg, Jeng-Shyang Pan
2021 — conf
Sequence-in-Sequence Learning for SOH Estimation of Lithium-Ion Battery.
CECNet
Thien Pham, Loi Truong, Mao Nguyen, Akhil Garg, Liang Gao, Tho Quan
2021 J jnl
Two infill criteria driven surrogate-assisted multi-objective evolutionary algorithms for computationally expensive problems with medium dimensions.
Swarm Evol. Comput.
Fan Li, Liang Gao, Akhil Garg, Weiming Shen, Shifeng Huang
2020 J jnl
Framework of model selection criteria approximated genetic programming for optimization function for renewable energy systems.
Swarm Evol. Comput.
Akhil Garg, Shaosen Su, Fan Li, Liang Gao
2020 J jnl
Multi-objective optimisation framework of genetic programming for investigation of bullwhip effect and net stock amplification for three-stage supply chain systems.
Int. J. Bio Inspired Comput.
Akhil Garg, Surinder Singh, Liang Gao, Mei-Juan Xu, Chee Pin Tan
2020 — book
Welding and Cutting Case Studies with Supervised Machine Learning
S. Arungalai Vendan, Rajeev Kamal, Abhinav Karan, Liang Gao, Xiaodong Niu, Akhil Garg
2019 J jnl
AHE Detection With a Hybrid Intelligence Model in Smart Healthcare.
IEEE Access
Guorong Xiao, Akhil Garg, Dicheng Chen, Dazhi Jiang, Wanneng Shu, Xuemiao Xu
2019 J jnl
Analysis and multi-objective optimization of a kind of teaching manipulator.
Swarm Evol. Comput.
Zhun Fan, Yugen You, Xinye Cai, Haodong Zheng, Guijie Zhu, Wenji Li, Akhil Garg, Kalyanmoy Deb, Erik D. Goodman
2019 J jnl
Crash analysis of lithium-ion batteries using finite element based neural search analytical models.
Eng. Comput.
V. Vijayaraghavan, Li Shui, Akhil Garg, Xiongbin Peng, Vikas Pratap Singh
2019 J jnl
Evaluation of genetic programming-based models for simulating bead dimensions in wire and arc additive manufacturing.
J. Intell. Manuf.
Biranchi Narayan Panda, K. Shankhwar, Akhil Garg, M. M. Savalani
2019 J jnl
Partial disassembly line balancing for energy consumption and profit under uncertainty.
Robotics Comput. Integr. Manuf.
Kaipu Wang, Xinyu Li, Liang Gao, Akhil Garg
2019 J jnl
Sensor-Assisted Weighted Average Ensemble Model for Detecting Major Depressive Disorder.
Sensors
Nivedhitha Mahendran, P. M. Durai Raj Vincent, Kathiravan Srinivasan, Chuan-Yu Chang, Akhil Garg, Liang Gao, Daniel Gutiérrez-Reina
2018 J jnl
A hybrid method for overlapping speech detection in classroom environment.
Comput. Appl. Eng. Educ.
Dazhi Jiang, Yifei Chen, Akhil Garg
2018 J jnl
An evolutionary framework in modelling of multi-output characteristics of the bone drilling process.
Neural Comput. Appl.
Akhil Garg, K. Shankhwar, Dazhi Jiang, V. Vijayaraghavan, Biranchi Narayan Panda, Sudhansu Sekhar Panda
2018 J jnl
Genetic programming for soil-fiber composite assessment.
Adv. Eng. Softw.
H. V. Kurugodu, Sanandam Bordoloi, Y. Hong, Ankit Garg, Akhil Garg, S. Sreedeep, Amir Hossein Gandomi
2018 J jnl
Laser power based surface characteristics models for 3-D printing process.
J. Intell. Manuf.
Akhil Garg, Jasmine Siu Lee Lam, M. M. Savalani
2017 J jnl
A hybrid computational intelligence framework in modelling of coal-oil agglomeration phenomenon.
Appl. Soft Comput.
Akhil Garg, Jasmine Siu Lee Lam, Biranchi Narayan Panda
2017 J jnl
Managing Information Uncertainty in Wave Height Modeling for the Offshore Structural Analysis through Random Set.
Complex.
Keqin Yan, Yi Zhang, Tao Cheng, Xianfeng Luo, Quan Zhou, Kun Fang, Ankit Garg, Akhil Garg
2017 — conf
Numerical Investigation of Flexural Properties of Curved Layer FDM Parts.
SocProS (2)
Xiongbin Peng, Biranchi Narayan Panda, Akhil Garg, H. Guan, M. M. Savalani
2017 J jnl
True stress measurement of nuclear fuel rod cladding material subjected to DSA regime.
Neural Comput. Appl.
Akhil Garg, Biranchi Narayan Panda, Kang Tai
2015 J jnl
A molecular simulation based computational intelligence study of a nano-machining process with implications on its environmental performance.
Swarm Evol. Comput.
Akhil Garg, V. Vijayaraghavan, Jasmine Siu Lee Lam, Pravin M. Singru, Liang Gao
2014 J jnl
A hybrid \(\text{ M}5^\prime \) -genetic programming approach for ensuring greater trustworthiness of prediction ability in modelling of FDM process.
J. Intell. Manuf.
Akhil Garg, Kang Tai, C. H. Lee, M. M. Savalani
2014 — conf
An Improved Multi-Gene Genetic Programming Approach for the Evolution of Generalized Model in Modelling of Rapid Prototyping Process.
IEA/AIE (1)
Akhil Garg, Kang Tai
2014 J jnl
An embedded simulation approach for modeling the thermal conductivity of 2D nanoscale material.
Simul. Model. Pract. Theory
Akhil Garg, V. Vijayaraghavan, Chee How Wong, Kang Tai, Liang Gao
2014 J jnl
An integrated SRM-multi-gene genetic programming approach for prediction of factor of safety of 3-D soil nailed slopes.
Eng. Appl. Artif. Intell.
Akhil Garg, Ankit Garg, Kang Tai, S. Sreedeep
2014 J jnl
Combined CI-MD approach in formulation of engineering moduli of single layer graphene sheet.
Simul. Model. Pract. Theory
Akhil Garg, V. Vijayaraghavan, Chee How Wong, Kang Tai, K. Sumithra, Liang Gao, Pravin M. Singru
2014 J jnl
Performance evaluation of microbial fuel cell by artificial intelligence methods.
Expert Syst. Appl.
Akhil Garg, V. Vijayaraghavan, S. S. Mahapatra, Kang Tai, Chee How Wong
2014 J jnl
Stepwise approach for the evolution of generalized genetic programming model in prediction of surface finish of the turning process.
Adv. Eng. Softw.
Akhil Garg, Kang Tai
2013 J jnl
Comparison of statistical and machine learning methods in modelling of data with multicollinearity.
Int. J. Model. Identif. Control.
Akhil Garg, Kang Tai
2013 — conf
Empirical analysis of model selection criteria for genetic programming in modeling of time series system.
CIFEr
Akhil Garg, S. Sriram, Kang Tai
2013 — conf
Genetic Programming for Modeling Vibratory Finishing Process: Role of Experimental Designs and Fitness Functions.
SEMCCO (2)
Akhil Garg, Kang Tai
2013 J jnl
Review of empirical modelling techniques for modelling of turning process.
Int. J. Model. Identif. Control.
Akhil Garg, Yogesh Bhalerao, Kang Tai
2013 C conf
Selection of a robust experimental design for the effective modeling of nonlinear systems using Genetic Programming.
CIDM
Akhil Garg, Kang Tai