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In this work, we present the new global QCD analyses, referred to asPKHFF.23, for charged pion, kaon, and unidentified light hadrons by utilizingthe Neural Network for fitting the high energy lepton-lepton and lepton-hadronscattering to determine parton-to-hadron fragmentation functions (FFs) at bothnext-to-leading-order (NLO) and next-to-next-to-leading-order (NNLO) accuracy.The analyses include all available single-inclusive $e^+e^-$ annihilation (SIA)and semi-inclusive deep-inelastic scattering (SIDIS) data for charged pions,kaons, and unidentified light hadrons. Considering the most recent nuclearparton distribution functions (nuclear PDFs) available in the literature, weassess the impact of nuclear corrections on the determination of light hadronsFFs. We show that considering the nuclear corrections at both NLO and NNLOaccuracy affect the central values of FFs and the associated uncertainty bands,and could improve the fit quality as well. The Neural Network parametrizationenriched with the Monte Carlo methodology for uncertainty estimations are usedfor all sources of experimental uncertainties and the proton PDFs.

Nuclear corrections on the charged hadron fragmentation functions in a Neural Network global QCD analysis