A data-driven framework integrating design of experiments, response surface methodology and machine learning for optimizing electric multifunctional cable stripping

This dataset contains structured experimental data and reproducibility code for machine learning-based optimization of electric multifunctional cable stripping parameters, supporting fiber optic performance analysis via Design of Experiments (Box-Behnken, CCD, Taguchi), Response Surface Methodology, and multi-objective optimization under ITU-T G.652/G.657 standards.