Open Access
| Issue |
E3S Web of Conf.
Volume 405, 2023
2023 International Conference on Sustainable Technologies in Civil and Environmental Engineering (ICSTCE 2023)
|
|
|---|---|---|
| Article Number | 02003 | |
| Number of page(s) | 12 | |
| Section | Renewable Energy & Electrical Technology | |
| DOI | https://doi.org/10.1051/e3sconf/202340502003 | |
| Published online | 26 July 2023 | |
- National Policy on Biofuels, Ministry of New & Renewable Energy, Government of India. [Google Scholar]
- Report on “Biofuel promotion in India for transport: Exploring the grey areas”, TERI, (2015) [Google Scholar]
- “Research and Development Report on Tree Born Oilseeds”, National Oilseeds and Vegetable Oils Development Board, Government of India (2009) [Google Scholar]
- Donald F. Specht, “A general regression neural network”, IEEE Transactions on Neural Networks, Vol. 2, No. 6 (1991) [Google Scholar]
- H. Majumder and K. P. Maity, “Predictive analysis on responses in WEDM of titanium grade 6 using general regression neural network (GRNN) and multiple regression analysis (MRA)”, Silicon. Vol.10, pp. 1763–1776 (2018). [CrossRef] [Google Scholar]
- Reza Rooki, “Application of general regression neural network (GRNN) for indirect measuring pressure loss of herschel–bulkley drilling fluids in oil drilling”, Measurement, Vol.85, pp.184–191 (2016). [CrossRef] [Google Scholar]
- Biranchi Narayan Panda, M. V. A. Raju Bahubalendruni and Bibhuti Bhusan Biswal, “A general regression neural network approach for the evaluation of compressive strength of FDM prototypes”, Neural Computing and Applications, Vol.26, pp.1129–1136 (2015) [CrossRef] [Google Scholar]
- Biranchi Narayan Panda, M. V. A. Raju Bahubalendruni and Bibhuti Bhusan Biswal, “A general regression neural network approach for the evaluation of compressive strength of FDM prototypes”, Neural Computing and Applications, Vol.26, pp.1129–1136 (2015) [CrossRef] [Google Scholar]
- Ling Kang, SibaoWang, ShilongWang, Chi Ma, Lili Yi and Haixu Zou, “Tool wear monitoring using generalized regression neural network”, Advances in Mechanical Engineering, Vol. 11(5), pp. 1–10 (2019) [Google Scholar]
- Ahmad Jobran AI-Mahasneh, Sreenatha G. Anavatti and Matthew A. Garratt, “Review of applications of generalized regression neural networks in identification and control of dynamic systems”, arXiv, (2018) [Google Scholar]
- Neha Sharma and Hari Om, “Usage of Probabilistic and General Regression Neural Network for Early Detection and Prevention of Oral Cancer”, The Scientific World Journal (2015) [Google Scholar]
- Raja Das and M.K Pradhan, “General regression neural network and back propagation neural network modelling for predicting radial overcut in EDM: A comparative study”, International Journal of Mechanical and Mechatronics Engineering, Vol.8, No.4 (2014) [Google Scholar]
- Chiranjeeva Rao Seela, B. Ravisankar and B.M.V.A. Raju, “A GRNN based frame work to test the influence of nano zinc additive biodiesel blends on CI engine performance and emissions”, Egyptian Journal of Petroleum, 2018, Vol. 27, pp. 641–647 (2018) [CrossRef] [Google Scholar]
- Harisankar Bendu B.B.V.L. Deepak and S. Murugan, “Application of GRNN for the prediction of performance and exhaust emissions in HCCI engine using ethanol”, Energy Conversion and Management, 2016, Vol. 122, pp. 165–173 (2016) [Google Scholar]
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