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Optimising the Indian Vehicle Supply Chain: a Comparative Study of RNN, CNN, and ANN Approaches

Yogendra Chhetri & Kabir Sharma

International Journal of Process Management and Benchmarking2025https://doi.org/10.1504/ijpmb.2025.10072922article
AJG 1
Weight
0.46

What the paper says

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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https://doi.org/https://doi.org/10.1504/ijpmb.2025.10072922

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@article{yogendra2025,
  title        = {{Optimising the Indian Vehicle Supply Chain: a Comparative Study of RNN, CNN, and ANN Approaches}},
  author       = {Yogendra Chhetri & Kabir Sharma},
  journal      = {International Journal of Process Management and Benchmarking},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijpmb.2025.10072922},
}

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Optimising the Indian Vehicle Supply Chain: a Comparative Study of RNN, CNN, and ANN Approaches

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Evidence weight

0.46

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.37 × 0.4 = 0.15
M · momentum0.60 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.