Genetic Programming Bibliography entries for Liang Gao
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Chee How Wong,
Pravin M Singru,
Jasmine Siu Lee Lam,
Biranchi Narayan Panda,
C M M Chin,
Kuldip Singh Sangwan,
Vikas Pratap Singh,
Genetic Programming Articles by Liang Gao
Akhil Garg and Shaosen Su and Fan Li and Liang Gao.
Framework of model selection criteria approximated genetic programming for optimization function for renewable energy systems.
Swarm and Evolutionary Computation, 59:100750, 2020.
Liu Yun and Ankit Goyal and Vikas Pratap Singh and Liang Gao and Xiongbin Peng and Xiaodong Niu and Chin-Tsan Wang and Akhil Garg.
Experimental coupled predictive modelling based recycling of waste printed circuit boards for maximum extraction of copper.
Journal of Cleaner Production, 218:763-771, 2019.
Liu Yun and Wei Li and Akhil Garg and Sivasriprasanna Maddila and Liang Gao and Zhun Fan and P. Buragohain and Chin-Tsan Wang.
Maximization of extraction of Cadmium and Zinc during recycling of spent battery mix: An application of combined genetic programming and simulated annealing approach.
Journal of Cleaner Production, 218:130-140, 2019.
Shrutidhara Sarma and Ankit Goyal and Liang Gao and Xiaodong Niu and Akhil Garg and Xu Meijuan and Jayne Sandoval.
Thermal performance of thin film heat gauges of gold, silver and nano-composite.
Applied Thermal Engineering, 147:545-550, 2019.
Akhil Garg and Li Wei and Ankit Goyal and Xujian Cui and Liang Gao.
Evaluation of batteries residual energy for battery pack recycling: Proposition of stack stress-coupled-AI approach.
Journal of Energy Storage, 26:101001, 2019.
Akhil Garg and Liang Gao and Wei Li and Surinder Singh and Xiongbin Peng and Xujian Cui and Z. Fan and Harpreet Singh and C. M. M. Chin.
Evolutionary framework design in formulation of decision support models for production emissions and net profit of firm: Implications on environmental concerns of supply chains.
Journal of Cleaner Production, 231:1136-1148, 2019.
V. Vijayaraghavan and Akhil Garg and Liang Gao.
Fracture mechanics modelling of lithium-ion batteries under pinch torsion test.
Measurement, 114:382-389, 2018.
Yuhao Huang and Liang Gao and Zhang Yi and Kang Tai and P. Kalita and Paweena Prapainainar and Akhil Garg.
An application of evolutionary system identification algorithm in modelling of energy production system.
Measurement, 114:122-131, 2018.
V. Vijayaraghavan and A. Garg and K. Tai and Liang Gao.
Thermo-mechanical modeling of metallic alloys for nuclear engineering applications.
Measurement, 97:242-250, 2017.
V. Vijayaraghavan and A. Garg and Liang Gao and R. Vijayaraghavan and Guoxing Lu.
A finite element based data analytics approach for modeling turning process of Inconel 718 alloys.
Journal of Cleaner Production, 137:1619-1627, 2016.
Akhil Garg and Shrutidhara Sarma and B. N. Panda and Jian Zhang and L. Gao.
Study of effect of nanofluid concentration on response characteristics of machining process for cleaner production.
Journal of Cleaner Production, 135:476-489, 2016.
Akhil1 Garg and Jasmine Siu Lee Lam and L. Gao.
Modeling multiple-response environmental and manufacturing characteristics of EDM process.
Journal of Cleaner Production, 137:1588-1601, 2016.
R. Vijayaraghavan and A. Garg and V. Vijayaraghavan and Liang Gao.
Development of energy consumption model of abrasive machining process by a combined evolutionary computing approach.
Measurement, 75:171-179, 2015.
Akhil1 Garg and V. Vijayaraghavan and Jasmine Siu Lee Lam and Pravin M Singru and Liang Gao.
A molecular simulation based computational intelligence study of a nano-machining process with implications on its environmental performance.
Swarm and Evolutionary Computation, 21:54-63, 2015.
Akhil1 Garg and Jasmine Siu Lee Lam and L. Gao.
Energy conservation in manufacturing operations: modelling the milling process by a new complexity-based evolutionary approach.
Journal of Cleaner Production, 108, Part A:34-45, 2015.
V. Vijayaraghavan and A. Garg and C. H. Wong and K. Tai and Pravin M. Singru and Liang Gao and K. S. Sangwan.
A molecular dynamics based artificial intelligence approach for characterizing thermal transport in nanoscale material.
Thermochimica Acta, 594:39-49, 2014.
A. Garg and V. Vijayaraghavan and C. H. Wong and K. Tai and K. Sumithra and L. Gao and Pravin M. Singru.
Combined CI-MD approach in formulation of engineering moduli of single layer graphene sheet.
Simulation Modelling Practice and Theory, 48:93-111, 2014.
A. Garg and V. Vijayaraghavan and C. H. Wong and K. Tai and Liang Gao.
An embedded simulation approach for modeling the thermal conductivity of 2D nanoscale material.
Simulation Modelling Practice and Theory, 44:1-13, 2014.
Yang Yang and Xinyu Li and Liang Gao and Xinyu Shao.
A new approach for predicting and collaborative evaluating the cutting force in face milling based on gene expression programming.
Journal of Network and Computer Applications, 36(6):1540-1550, 2013.
X. Y. Li and X. Y. Shao and L. Gao.
Optimization of flexible process planning by genetic programming.
The International Journal of Advanced Manufacturing Technology, 38(1-2):143-153, 2008.
Genetic Programming conference papers by Liang Gao
Long Wen and Liang Gao and Xinyu Li and Guohui Zhang and Yang Yang.
Application of Free Pattern Search on the Surface Roughness Prediction in End Milling. In
Xiaodong Li editor,
Proceedings of the 2012 IEEE Congress on Evolutionary Computation, pages 765-770, Brisbane, Australia, 2012.
Li Nie and Liang Gao and Peigen Li and Liping Zhang.
Application of gene expression programming on dynamic job shop scheduling problem. In
15th International Conference on Computer Supported Cooperative Work in Design (CSCWD 2011), pages 291-295, Lausanne, 2011. IEEE.