Selection of a robust experimental design for the effective modeling of nonlinear systems using Genetic Programming. - Akhil Garg 002; Kang Tai (CIDM, 2013)

Empirical analysis of model selection criteria for genetic programming in modeling of time series system. - Akhil Garg 002; S. Sriram; Kang Tai (CIFEr, 2013)

Genetic Programming for Modeling Vibratory Finishing Process: Role of Experimental Designs and Fitness Functions. - Akhil Garg 002; Kang Tai (SEMCCO (2), 2013)

Review of empirical modelling techniques for modelling of turning process. - Akhil Garg 002; Yogesh Bhalerao; Kang Tai (Int. J. Model. Identif. Control., 2013)

Comparison of statistical and machine learning methods in modelling of data with multicollinearity. - Akhil Garg 002; Kang Tai (Int. J. Model. Identif. Control., 2013)

An Improved Multi-Gene Genetic Programming Approach for the Evolution of Generalized Model in Modelling of Rapid Prototyping Process. - Akhil Garg 002; Kang Tai (IEA/AIE (1), 2014)

Stepwise approach for the evolution of generalized genetic programming model in prediction of surface finish of the turning process. - Akhil Garg 002; Kang Tai (Adv. Eng. Softw., 2014)

An integrated SRM-multi-gene genetic programming approach for prediction of factor of safety of 3-D soil nailed slopes. - Akhil Garg 002; Ankit Garg; Kang Tai; S. Sreedeep (Eng. Appl. Artif. Intell., 2014)

Performance evaluation of microbial fuel cell by artificial intelligence methods. - Akhil Garg 002; V. Vijayaraghavan; S. S. Mahapatra; Kang Tai; C. H. Wong (Expert Syst. Appl., 2014)

A hybrid ( text{ M}5^ prime ) -genetic programming approach for ensuring greater trustworthiness of prediction ability in modelling of FDM process. - Akhil Garg 002; Kang Tai; C. H. Lee; M. M. Savalani (J. Intell. Manuf., 2014)

An embedded simulation approach for modeling the thermal conductivity of 2D nanoscale material. - Akhil Garg 002; V. Vijayaraghavan; C. H. Wong; Kang Tai; Liang Gao 001 (Simul. Model. Pract. Theory, 2014)

Combined CI-MD approach in formulation of engineering moduli of single layer graphene sheet. - Akhil Garg 002; V. Vijayaraghavan; C. H. Wong; Kang Tai; K. Sumithra; Liang Gao 001; Pravin M. Singru (Simul. Model. Pract. Theory, 2014)

A molecular simulation based computational intelligence study of a nano-machining process with implications on its environmental performance. - Akhil Garg 002; V. Vijayaraghavan; Jasmine Siu Lee Lam; Pravin M. Singru; Liang Gao 001 (Swarm Evol. Comput., 2015)

Numerical Investigation of Flexural Properties of Curved Layer FDM Parts. - Xiongbin Peng; Biranchi Narayan Panda; Akhil Garg 002; H. Guan; M. M. Savalani (SocProS (2), 2017)

A hybrid computational intelligence framework in modelling of coal-oil agglomeration phenomenon. - Akhil Garg 002; Jasmine Siu Lee Lam; Biranchi Narayan Panda (Appl. Soft Comput., 2017)

Managing Information Uncertainty in Wave Height Modeling for the Offshore Structural Analysis through Random Set. - Keqin Yan; Yi Zhang 019; Tao Cheng; Xianfeng Luo; Quan Zhou; Kun Fang; Ankit Garg; Akhil Garg 002 (Complex., 2017)

True stress measurement of nuclear fuel rod cladding material subjected to DSA regime. - Akhil Garg 002; Biranchi Narayan Panda; Kang Tai (Neural Comput. Appl., 2017)

Genetic programming for soil-fiber composite assessment. - H. V. Kurugodu; Sanandam Bordoloi; Y. Hong; Ankit Garg; Akhil Garg 002; S. Sreedeep; Amir Hossein Gandomi (Adv. Eng. Softw., 2018)

A hybrid method for overlapping speech detection in classroom environment. - Dazhi Jiang; Yifei Chen; Akhil Garg 002 (Comput. Appl. Eng. Educ., 2018)

Laser power based surface characteristics models for 3-D printing process. - Akhil Garg 002; Jasmine Siu Lee Lam; M. M. Savalani (J. Intell. Manuf., 2018)

An evolutionary framework in modelling of multi-output characteristics of the bone drilling process. - Akhil Garg 002; K. Shankhwar; Dazhi Jiang; V. Vijayaraghavan; Biranchi Narayan Panda; Sudhansu Sekhar Panda (Neural Comput. Appl., 2018)

AHE Detection With a Hybrid Intelligence Model in Smart Healthcare. - Guorong Xiao; Akhil Garg 002; Dicheng Chen; Dazhi Jiang; Wanneng Shu; Xuemiao Xu (IEEE Access, 2019)

Crash analysis of lithium-ion batteries using finite element based neural search analytical models. - V. Vijayaraghavan; Li Shui; Akhil Garg 002; Xiongbin Peng; Vikas Pratap Singh (Eng. Comput., 2019)

Evaluation of genetic programming-based models for simulating bead dimensions in wire and arc additive manufacturing. - Biranchi Narayan Panda; K. Shankhwar; Akhil Garg 002; M. M. Savalani (J. Intell. Manuf., 2019)

Partial disassembly line balancing for energy consumption and profit under uncertainty. - Kaipu Wang; Xinyu Li 001; Liang Gao 001; Akhil Garg 002 (Robotics Comput. Integr. Manuf., 2019)

Sensor-Assisted Weighted Average Ensemble Model for Detecting Major Depressive Disorder. - Nivedhitha Mahendran; P. M. Durai Raj Vincent; Kathiravan Srinivasan; Chuan-Yu Chang; Akhil Garg 002; Liang Gao 001; Daniel Gutiérrez-Reina (Sensors, 2019)

Analysis and multi-objective optimization of a kind of teaching manipulator. - Zhun Fan; Yugen You; Xinye Cai; Haodong Zheng; Guijie Zhu; Wenji Li; Akhil Garg 002; Kalyanmoy Deb; Erik D. Goodman (Swarm Evol. Comput., 2019)

Welding and Cutting Case Studies with Supervised Machine Learning - S. Arungalai Vendan; Rajeev Kamal; Abhinav Karan; Liang Gao 001; Xiaodong Niu; Akhil Garg 002 (Springer, 2020)

Multi-objective optimisation framework of genetic programming for investigation of bullwhip effect and net stock amplification for three-stage supply chain systems. - Akhil Garg 002; Surinder Singh; Liang Gao 001; Mei-Juan Xu; Chee Pin Tan (Int. J. Bio Inspired Comput., 2020)

Framework of model selection criteria approximated genetic programming for optimization function for renewable energy systems. - Akhil Garg 002; Shaosen Su; Fan Li; Liang Gao 001 (Swarm Evol. Comput., 2020)

Sequence-in-Sequence Learning for SOH Estimation of Lithium-Ion Battery. - Thien Pham; Loi Truong; Mao Nguyen; Akhil Garg 002; Liang Gao 001; Tho Quan 001 (CECNet, 2021)

A comparative study of pre-screening strategies within a surrogate-assisted multi-objective algorithm framework for computationally expensive problems. - Fan Li; Liang Gao 001; Akhil Garg 002; Weiming Shen 001; Shifeng Huang (Neural Comput. Appl., 2021)

Two infill criteria driven surrogate-assisted multi-objective evolutionary algorithms for computationally expensive problems with medium dimensions. - Fan Li; Liang Gao 001; Akhil Garg 002; Weiming Shen 001; Shifeng Huang (Swarm Evol. Comput., 2021)

A New Approach to Solve Uncertain Multidisciplinary Design Optimization Based on Conditional Value at Risk. - Wei Li 173; Mi Xiao; Akhil Garg 002; Liang Gao 001 (IEEE Trans Autom. Sci. Eng., 2021)

Hybrid Strategy of Multiple Optimization Algorithms Applied to 3-D Terrain Node Coverage of Wireless Sensor Network. - Li-Gang Zhang; Fang Fan; Shu-Chuan Chu; Akhil Garg 002; Jeng-Shyang Pan 001 (Wirel. Commun. Mob. Comput., 2021)

Conceptualizing A Battery Swapping Station: A Case Study in Malaysia. - Elvin Cheah Ee Sheng; Christina Chin May May; Novita Sakundarini; Akhil Garg 002 (IICAIET, 2022)

Multidisciplinary robust design optimization considering parameter and metamodeling uncertainties. - Wei Li 173; Liang Gao 001; Akhil Garg 002; Mi Xiao (Eng. Comput., 2022)

Surrogate-assisted multi-objective evolutionary optimization with a multi-offspring method and two infill criteria. - Fan Li; Liang Gao 001; Weiming Shen 001; Akhil Garg 002 (Swarm Evol. Comput., 2023)

A Machine Learning Approach for Energy-Efficient Intelligent Transportation Scheduling Problem in a Real-World Dynamic Circumstances. - Jianhui Mou; Kaizhou Gao; Peiyong Duan; Junqing Li 001; Akhil Garg 002; Rohit Sharma 002 (IEEE Trans. Intell. Transp. Syst., 2023)

Tropical modeling of battery swapping and charging station. - Nikolai K. Krivulin; Akhil Garg 002 (CoRR, 2024)

Risk-Based Design Optimization via Scenario Generation and Genetic Programming Under Hybrid Uncertainties. - Wei Li 173; Xiaowei Zhou; Haihong Huang; Akhil Garg 002; Liang Gao 001 (J. Comput. Inf. Sci. Eng., 2024)