Akhil Garg

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 27

Top Topics

Thermal Conductivity

Bullwhip Effect

Computational Intelligence

Genetic Programming

Top Venues

Swarm Evol. Comput.

J. Intell. Manuf.

Neural Comput. Appl.

Publications

Wei Li, Xiaowei Zhou, Haihong Huang, Akhil Garg, Liang Gao
Risk-Based Design Optimization via Scenario Generation and Genetic Programming Under Hybrid Uncertainties. J. Comput. Inf. Sci. Eng. 24 (10) (2024)
Nikolai K. Krivulin, Akhil Garg
Tropical modeling of battery swapping and charging station. CoRR (2024)
Fan Li, Liang Gao, Weiming Shen, Akhil Garg
Surrogate-assisted multi-objective evolutionary optimization with a multi-offspring method and two infill criteria. Swarm Evol. Comput. 79 (2023)
Jianhui Mou, Kaizhou Gao, Peiyong Duan, Junqing Li, Akhil Garg, Rohit Sharma
A Machine Learning Approach for Energy-Efficient Intelligent Transportation Scheduling Problem in a Real-World Dynamic Circumstances. IEEE Trans. Intell. Transp. Syst. 24 (12) (2023)
Elvin Cheah Ee Sheng, Christina Chin May May, Novita Sakundarini, Akhil Garg
Conceptualizing A Battery Swapping Station: A Case Study in Malaysia. IICAIET (2022)
Wei Li, Liang Gao, Akhil Garg, Mi Xiao
Multidisciplinary robust design optimization considering parameter and metamodeling uncertainties. Eng. Comput. 38 (1) (2022)
Fan Li, Liang Gao, Akhil Garg, Weiming Shen, Shifeng Huang
Two infill criteria driven surrogate-assisted multi-objective evolutionary algorithms for computationally expensive problems with medium dimensions. Swarm Evol. Comput. 60 (2021)
Li-Gang Zhang, Fang Fan, Shu-Chuan Chu, Akhil Garg, Jeng-Shyang Pan
Hybrid Strategy of Multiple Optimization Algorithms Applied to 3-D Terrain Node Coverage of Wireless Sensor Network. Wirel. Commun. Mob. Comput. 2021 (2021)
Fan Li, Liang Gao, Akhil Garg, Weiming Shen, Shifeng Huang
A comparative study of pre-screening strategies within a surrogate-assisted multi-objective algorithm framework for computationally expensive problems. Neural Comput. Appl. 33 (9) (2021)
Wei Li, Mi Xiao, Akhil Garg, Liang Gao
A New Approach to Solve Uncertain Multidisciplinary Design Optimization Based on Conditional Value at Risk. IEEE Trans Autom. Sci. Eng. 18 (1) (2021)
Thien Pham, Loi Truong, Mao Nguyen, Akhil Garg, Liang Gao, Tho Quan
Sequence-in-Sequence Learning for SOH Estimation of Lithium-Ion Battery. CECNet (2021)
Akhil Garg, Surinder Singh, Liang Gao, Mei-Juan Xu, Chee Pin Tan
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. 16 (4) (2020)
Akhil Garg, Shaosen Su, Fan Li, Liang Gao
Framework of model selection criteria approximated genetic programming for optimization function for renewable energy systems. Swarm Evol. Comput. 59 (2020)
V. Vijayaraghavan, Li Shui, Akhil Garg, Xiongbin Peng, Vikas Pratap Singh
Crash analysis of lithium-ion batteries using finite element based neural search analytical models. Eng. Comput. 35 (1) (2019)
Nivedhitha Mahendran, P. M. Durai Raj Vincent, Kathiravan Srinivasan, Chuan-Yu Chang, Akhil Garg, Liang Gao, Daniel Gutiérrez-Reina
Sensor-Assisted Weighted Average Ensemble Model for Detecting Major Depressive Disorder. Sensors 19 (22) (2019)
Kaipu Wang, Xinyu Li, Liang Gao, Akhil Garg
Partial disassembly line balancing for energy consumption and profit under uncertainty. Robotics Comput. Integr. Manuf. 59 (2019)
Biranchi Narayan Panda, K. Shankhwar, Akhil Garg, M. M. Savalani
Evaluation of genetic programming-based models for simulating bead dimensions in wire and arc additive manufacturing. J. Intell. Manuf. 30 (2) (2019)
Zhun Fan, Yugen You, Xinye Cai, Haodong Zheng, Guijie Zhu, Wenji Li, Akhil Garg, Kalyanmoy Deb, Erik D. Goodman
Analysis and multi-objective optimization of a kind of teaching manipulator. Swarm Evol. Comput. 50 (2019)
Guorong Xiao, Akhil Garg, Dicheng Chen, Dazhi Jiang, Wanneng Shu, Xuemiao Xu
AHE Detection With a Hybrid Intelligence Model in Smart Healthcare. IEEE Access 7 (2019)
Akhil Garg, Jasmine Siu Lee Lam, M. M. Savalani
Laser power based surface characteristics models for 3-D printing process. J. Intell. Manuf. 29 (6) (2018)
H. V. Kurugodu, Sanandam Bordoloi, Y. Hong, Ankit Garg, Akhil Garg, S. Sreedeep, Amir Hossein Gandomi
Genetic programming for soil-fiber composite assessment. Adv. Eng. Softw. 122 (2018)
Dazhi Jiang, Yifei Chen, Akhil Garg
A hybrid method for overlapping speech detection in classroom environment. Comput. Appl. Eng. Educ. 26 (1) (2018)
Akhil Garg, K. Shankhwar, Dazhi Jiang, V. Vijayaraghavan, Biranchi Narayan Panda, Sudhansu Sekhar Panda
An evolutionary framework in modelling of multi-output characteristics of the bone drilling process. Neural Comput. Appl. 29 (11) (2018)
Keqin Yan, Yi Zhang, Tao Cheng, Xianfeng Luo, Quan Zhou, Kun Fang, Ankit Garg, Akhil Garg
Managing Information Uncertainty in Wave Height Modeling for the Offshore Structural Analysis through Random Set. Complex. 2017 (2017)
Xiongbin Peng, Biranchi Narayan Panda, Akhil Garg, H. Guan, M. M. Savalani
Numerical Investigation of Flexural Properties of Curved Layer FDM Parts. SocProS (2) (2017)
Akhil Garg, Biranchi Narayan Panda, Kang Tai
True stress measurement of nuclear fuel rod cladding material subjected to DSA regime. Neural Comput. Appl. 28 (S-1) (2017)
Akhil Garg, Jasmine Siu Lee Lam, Biranchi Narayan Panda
A hybrid computational intelligence framework in modelling of coal-oil agglomeration phenomenon. Appl. Soft Comput. 55 (2017)
Akhil Garg, V. Vijayaraghavan, Jasmine Siu Lee Lam, Pravin M. Singru, Liang Gao
A molecular simulation based computational intelligence study of a nano-machining process with implications on its environmental performance. Swarm Evol. Comput. 21 (2015)
Akhil Garg, V. Vijayaraghavan, C. H. Wong, Kang Tai, Liang Gao
An embedded simulation approach for modeling the thermal conductivity of 2D nanoscale material. Simul. Model. Pract. Theory 44 (2014)
Akhil Garg, Kang Tai
An Improved Multi-Gene Genetic Programming Approach for the Evolution of Generalized Model in Modelling of Rapid Prototyping Process. IEA/AIE (1) (2014)
Akhil Garg, V. Vijayaraghavan, S. S. Mahapatra, Kang Tai, C. H. Wong
Performance evaluation of microbial fuel cell by artificial intelligence methods. Expert Syst. Appl. 41 (4) (2014)
Akhil Garg, Kang Tai
Stepwise approach for the evolution of generalized genetic programming model in prediction of surface finish of the turning process. Adv. Eng. Softw. 78 (2014)
Akhil Garg, V. Vijayaraghavan, C. H. Wong, Kang Tai, K. Sumithra, Liang Gao, Pravin M. Singru
Combined CI-MD approach in formulation of engineering moduli of single layer graphene sheet. Simul. Model. Pract. Theory 48 (2014)
Akhil Garg, Kang Tai, C. H. Lee, M. M. Savalani
A hybrid \(\text{ M}5^\prime \) -genetic programming approach for ensuring greater trustworthiness of prediction ability in modelling of FDM process. J. Intell. Manuf. 25 (6) (2014)
Akhil Garg, Ankit Garg, Kang Tai, S. Sreedeep
An integrated SRM-multi-gene genetic programming approach for prediction of factor of safety of 3-D soil nailed slopes. Eng. Appl. Artif. Intell. 30 (2014)
Akhil Garg, Kang Tai
Genetic Programming for Modeling Vibratory Finishing Process: Role of Experimental Designs and Fitness Functions. SEMCCO (2) (2013)
Akhil Garg, S. Sriram, Kang Tai
Empirical analysis of model selection criteria for genetic programming in modeling of time series system. CIFEr (2013)
Akhil Garg, Yogesh Bhalerao, Kang Tai
Review of empirical modelling techniques for modelling of turning process. Int. J. Model. Identif. Control. 20 (2) (2013)
Akhil Garg, Kang Tai
Selection of a robust experimental design for the effective modeling of nonlinear systems using Genetic Programming. CIDM (2013)
Akhil Garg, Kang Tai
Comparison of statistical and machine learning methods in modelling of data with multicollinearity. Int. J. Model. Identif. Control. 18 (4) (2013)