Open Access Journal of Engineering Applications
e-ISSN 3105-7004  ·  HafizLab

On Thin-Film Solar Cells

Farhana Mensah Corresponding
National Institute of Technology Tiruchirappalli
Neha Mehta
University of Moratuwa
Priya Dlamini
Technical University of Munich

Abstract

Rapid urbanisation and industrial expansion have made thin-film solar cells an increasingly important concern for manufacturing processes. Convolutional neural network was applied to a series of test cases representative of manufacturing processes. The optimised parameters raised the useful output by 45% while simultaneously reducing the overall losses. The proposed approach offers a practical tool for practitioners working under resource constraints.
Keywords: thin-film solar cellsconvolutional neural networknatural fibre compositerainfall-runoff modelling

References

  1. Karimi, R., & Nasser, A. (2003). Municipal solid waste in highway pavement design. International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT), 26(2), 286-297.
  2. Al-Rashid, Y., Rao, H., & Kumar, C. (1994). Image segmentation in earthquake-resistant design. IEEE Transactions on Industrial Electronics, 32(3), 667-681.

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