Elenco delle pubblicazioni

Sgarro, G. A., Santoro, D., & Grilli, L. (2026). "Ant colony optimization for solving mixed Chinese postman problem on open real world data." Neural Computing & Applications, 38, 134. https://doi.org/10.1007/s00521-026-11846-1

Sgarro, G. A., Vasco, P., Santoro, D., Grilli, L., Giglio, M., Brunetti, N. D., Traetta, L., Cibelli, G., & Valenzano, A. A. (2026). "Identifying risk patterns for sudden cardiac death in athletes: A clustering and principal component analysis approach." PLOS ONE, 21(1): e0339377. https://doi.org/10.1371/journal.pone.0339377

Sgarro, G. A., Santoro, D., Colasanto, F., Grilli, L., Russo, C., Cappelletti, G. M., Cusenza, M., & Vairo, A. (2025). "Comparing Distance- and CO₂-Optimized Heuristics and Metaheuristics for the Multi-Depot Capacitated Vehicle Routing Problem in Agricultural Logistics." Proceedings of the 11th International Conference on Economics, Business & Management (ICEBM), pp. 240–250. https://doi.org/10.56065/ICEBM2025.240

Imperatrice, R. C. F., Melchiorre, L., Lorusso, D., Santoro, D., & Grilli, L. (2025). "Beyond the traditional classroom: innovation and inclusion in math teaching with AI." Journal of Inclusive Methodology and Technology in Learning and Teaching, 5(3).

Alderighi, M., Ciano, T., Ferrara, M., & Santoro, D. (2025). "MONTUR project: dataset for understanding and forecasting tourist flows." PLOS ONE, 20(10): e0335190. https://doi.org/10.1371/journal.pone.0335190

Anyebe, D., Di Bari, A., Santoro, D., & Villani, G. (2025). "A PPP Projects Valuation: Real Options, Competition and Anchoring Bias." Computational Economics. https://doi.org/10.1007/s10614-025-11109-6

Santoro, D., Grilli, L., Sgarro, G. A., Colasanto, F., & Villani, G. (2025). "MCMC Approach for Stock Price Forecasting Using an Italian-BERT Model." In A. Pollice & P. Mariani (Eds.), Methodological and Applied Statistics and Demography II (SIS 2024). Springer, Cham. https://doi.org/10.1007/978-3-031-64350-7_96

Di Bari, A., Grilli, L., Santoro, D., & Villani, G. (2024). "A new methodology to support wind investment decision: a combination of natural language processing and Monte Carlo option pricing technique." Decisions in Economics and Finance. https://doi.org/10.1007/s10203-024-00486-6

Santoro, D., Ciano, T., & Ferrara, M. (2024). "A comparison between machine and deep learning models on high stationarity data." Scientific Reports, 14, 19409. https://doi.org/10.1038/s41598-024-70341-6

Di Bari, A., Grilli, L., Santoro, D., & Villani, G. (2024). "A Combination of NLP and Monte Carlo Technique to Improve Wind Investment Decisions." In M. Corazza et al. (Eds.), Mathematical and Statistical Methods for Actuarial Sciences and Finance (MAF 2024). Springer, Cham. https://doi.org/10.1007/978-3-031-64273-9_20

Sgarro, G. A., Santoro, D., & Grilli, L. (2024). "Ant Colony Optimization for solving Directed Chinese Postman Problem." Neural Computing & Applications, 36, 17615–17630. https://doi.org/10.1007/s00521-024-10052-1

Guarino, A., Santoro, D., Grilli, L., Zaccagnino, R., & Balbi, M. (2024). "EvoFolio: a portfolio optimization method based on multi-objective evolutionary algorithms." Neural Computing & Applications, 36, 7221–7243. https://doi.org/10.1007/s00521-024-09456-w

Sgarro, G. A., Grilli, L., & Santoro, D. (2024). "Optimal multivariate mixture: a genetic algorithm approach." Annals of Operations Research. https://doi.org/10.1007/s10479-024-06045-x

Cappelletti, M. G., Caputo, R., Cariglia, M., Grilli, L., Russo, C., Santoro, D., & Sgarro, G. A. (2023). "Harnessing the power of blockchain in the agri-food sector: a meta-analysis of current research and best practices." Applied Mathematical Sciences, 17(10), 477–501. https://doi.org/10.12988/ams.2023.917473

Di Bari, A., Santoro, D., Tarrazon-Rodon, M. A., & Villani, G. (2024). "The impact of polarity score on real option valuation for multistage projects." Quality & Quantity, 58, 57–76. https://doi.org/10.1007/s11135-023-01635-6

Guarino, A., Grilli, L., Santoro, D., Messina, F., & Zaccagnino, R. (2024). "On the efficacy of 'herd behavior' in the commodities market: A neuro-fuzzy agent 'herding' on deep learning traders." Applied Stochastic Models in Business and Industry, 40(2), 348–372. https://doi.org/10.1002/asmb.2793

Cappelletti, G. M., Grilli, L., Russo, C., & Santoro, D. (2023). "Benchmarking Sustainable Mobility in Higher Education." Sustainability, 15(6), 5190. https://doi.org/10.3390/su15065190

Cappelletti, G. M., Grilli, L., Santoro, D., & Russo, C. (2022). "Machine learning and sustainable mobility: The case of the University of Foggia (Italy)." Applied Sciences, 12(17):8774. https://doi.org/10.3390/app12178774

Grilli, L., & Santoro, D. (2022). "Forecasting Financial Time Series with Boltzmann Entropy through Neural Networks." Computational Management Sciences, 19, 665–681. https://doi.org/10.1007/s10287-022-00430-2

Colasanto, F., Grilli, L., & Santoro, D. (2022). "Directional derivatives in non-Hausdorff TVS: topological filter techniques without metric structures." Applied Mathematical Sciences, 16(5), 251–260. https://doi.org/10.12988/ams.2022.916795

Colasanto, F., Grilli, L., Santoro, D., & Villani, G. (2022). "A neural network contribute to reverse cryptographic processes in bitcoin systems: attention on SHA256." Applied Mathematical Sciences, 16(4), 215–232. https://doi.org/10.12988/ams.2022.916778

Guarino, A., Grilli, L., Santoro, D., Messina, F., & Zaccagnino, R. (2022). "To learn or not to learn? Evaluating autonomous, adaptive, automated traders in cryptocurrencies financial bubbles." Neural Computing & Applications, 34, 20715–20756. https://doi.org/10.1007/s00521-022-07543-4

Colasanto, F., Grilli, L., Santoro, D., & Villani, G. (2022). "BERT’s sentiment score for portfolio optimization: A fine-tuned view in Black–Litterman model." Neural Computing & Applications, 34, 17507–17521. https://doi.org/10.1007/s00521-022-07403-1

Santoro, D., & Grilli, L. (2022). "Generative adversarial network to evaluate quantity of information in financial markets." Neural Computing & Applications, 34, 17473–17490. https://doi.org/10.1007/s00521-022-07401-3

Colasanto, F., Grilli, L., Santoro, D., & Villani, G. (2022). "AlBERTino for stock price prediction: A Gibbs sampling approach." Information Sciences, 597, 341–357. https://doi.org/10.1016/j.ins.2022.03.051

Santoro, D., & Villani, G. (2022). "Real R&D options under sentimental information analysis." In M. Corazza (Ed.), MAF 2022 – Mathematical and Statistical Methods for Actuarial Sciences and Finance, Chap. 67, pp. 1–6. Springer Nature Switzerland AG.

Cappelletti, G. M., Grilli, L., Santoro, D., & Russo, C. (2021). "Sustainable mobility in universities: The case of the University of Foggia (Italy)." Environments, 8, 57.

Grilli, L., & Santoro, D. (2021). "A statistical ensemble based approach for entropy in cryptocurrencies markets." Chaotic Modeling and Simulation (CMSIM), 2, 91–103.

Grilli, L., & Santoro, D. (2021). "Cryptocurrencies markets and entropy: A statistical ensemble based approach." Applied Mathematical Sciences, 15(7), 297–320.

Casalino, G., Grilli, L., Limone, P., Santoro, D., & Schicchi, D. (2021). "Deep learning for knowledge tracing in learning analytics: An overview." Proceedings of the First Workshop on Technology Enhanced Learning Environments for Blended Education (teleXbe 2021), Vol. 2817, CEUR Workshop Proceedings.

Grilli, L., & Santoro, D. (2021). "A statistical ensemble based approach for entropy in cryptocurrencies markets." Proceedings of the 13th International Chaotic Modeling and Simulation International Conference, p. 1091.

Grilli, L., & Santoro, D. (2021). "Machine-deep learning and finance: A review of recent results." Proceedings of the 4th International Conference on Mathematical and Related Sciences (ICMRS 2021).

Grilli, L., & Santoro, D. (2020). "Generative adversarial network for market hourly discrimination." Proceedings of the 3rd International Conference on Mathematical and Related Sciences (ICMRS 2020), pp. 106–113.