Genetic Programming Bibliography entries for Marco Russo

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GP coauthors/coeditors: Francesco Pio Barone, Daniele Dell'Aquila, Enrico Buccheri, Giuseppe Campobello, Antonino Segreto, Brunilde Gnoffo, Ivano Lombardo, Francesco Porto, Luigi Redigolo, G Leotta, P M Pugliatti, G Gigliucci,

Genetic Programming Articles by Marco Russo

  1. Ivano Lombardo and Daniele Dell'Aquila and Brunilde Gnoffo and Luigi Redigolo and Francesco Porto and Marco Russo. Universal Models for Heavy-Ion Fusion Cross Section Above-Barrier. EPJ Web of Conferences, 290:Article Number: 02017, 2023. details

  2. Daniele Dell'Aquila and Brunilde Gnoffo and Ivano Lombardo and Francesco Porto and Luigi Redigolo and Marco Russo. Understanding Heavy-ion Fusion Cross Section Data Using Novel Artificial Intelligence Approaches. Journal of Physics: Conference Series, 2619(1):012004, 2023. 44th Symposium on Nuclear Physics Cocoyoc. details

  3. Francesco Pio Barone and Daniele Dell'Aquila and Marco Russo. A novel multi-layer modular approach for real-time fuzzy-identification of gravitational-wave signals. Machine Learning: Science and Technology, 4(4):045054, 2023. details

  4. Daniele Dell'Aquila and Brunilde Gnoffo and Ivano Lombardo and Francesco Porto and Marco Russo. Modeling Heavy-Ion Fusion Cross Section Data via a Novel Artificial Intelligence Approach. Journal of Physics G: Nuclear and Particle Physics, 50(1):015101, 2022. details

  5. Enrico Buccheri and Daniele Dell'Aquila and Marco Russo. Stratified analysis of the age-related waist circumference cut-off model for the screening of dysglycemia at zero-cost. Obesity Medicine, 31:100398, 2022. details

  6. D. Dell'Aquila and M. Russo. Automatic classification of nuclear physics data via a Constrained Evolutionary Clustering approach. Computer Physics Communications, 259:107667, 2021. details

  7. Enrico Buccheri and Daniele Dell'Aquila and Marco Russo. Artificial intelligence in health data analysis: The Darwinian evolution theory suggests an extremely simple and zero-cost large-scale screening tool for prediabetes and type 2 diabetes. Diabetes Research and Clinical Practice, 174:108722, 2021. details

  8. Marco Russo. A novel technique to self-adapt parameters in parallel/distributed genetic programming. Soft Computing, 24(22):16885-16894, 2020. details

  9. Giuseppe Campobello and Daniele Dell'Aquila and Marco Russo and Antonino Segreto. Neuro-genetic programming for multigenre classification of music content. Applied Soft Computing, 94:106488, 2020. details

  10. Marco Russo. A distributed neuro-genetic programming tool. Swarm and Evolutionary Computation, 27:145-155, 2016. details

  11. M. Russo and G. Leotta and P. M. Pugliatti and G. Gigliucci. Genetic programming for photovoltaic plant output forecasting. Solar Energy, 105:264-273, 2014. details

Genetic Programming conference papers by Marco Russo