Data-driven multi-response optimization of locust bean pulp brake-pad composites using Taguchi L25 design, machine learning and SHAP explainability

Chike Martins Atah¹

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DOI: 10.21203/rs.3.rs-10670801/v1
Published: 2026-08-27
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Publisher: Springer Science and Business Media LLC
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Cite this work

BibTeX

@article{allodium:10.21203/rs.3.rs-10670801/v1,
  title = {Data-driven multi-response optimization of locust bean pulp brake-pad composites using Taguchi L25 design, machine learning and SHAP explainability},
  author = {Chike Martins Atah¹},
  year = {2026},
  doi = {10.21203/rs.3.rs-10670801/v1},
  url = {https://doi.org/10.21203/rs.3.rs-10670801/v1}
}

RIS

TY  - JOUR
TI  - Data-driven multi-response optimization of locust bean pulp brake-pad composites using Taguchi L25 design, machine learning and SHAP explainability
AU  - Chike Martins Atah¹
PY  - 2026
DO  - 10.21203/rs.3.rs-10670801/v1
UR  - https://doi.org/10.21203/rs.3.rs-10670801/v1
ER  -

APA

Atah¹, C. M. (2026). Data-driven multi-response optimization of locust bean pulp brake-pad composites using Taguchi L25 design, machine learning and SHAP explainability. https://doi.org/10.21203/rs.3.rs-10670801/v1

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crossref · retrieved 2026-09-25T22:27:42.110Z