Molero, G.D.; Poveda-Reyes, S.; Malviya, A.K.; GarcĂa-JimĂ©nez, E.; Leva, M.C.; Santarremigia, F.E.
Computational Solutions Based on Bayesian Networks to Hierarchize and to Predict Factors Influencing Gender Fairness in the Transport System: Four Use Cases. Sustainability 2021, 13, 11372.
https://doi.org/10.3390/su132011372
AMA Style
Molero GD, Poveda-Reyes S, Malviya AK, GarcĂa-JimĂ©nez E, Leva MC, Santarremigia FE.
Computational Solutions Based on Bayesian Networks to Hierarchize and to Predict Factors Influencing Gender Fairness in the Transport System: Four Use Cases. Sustainability. 2021; 13(20):11372.
https://doi.org/10.3390/su132011372
Chicago/Turabian Style
Molero, Gemma Dolores, Sara Poveda-Reyes, Ashwani Kumar Malviya, Elena GarcĂa-JimĂ©nez, Maria Chiara Leva, and Francisco Enrique Santarremigia.
2021. "Computational Solutions Based on Bayesian Networks to Hierarchize and to Predict Factors Influencing Gender Fairness in the Transport System: Four Use Cases" Sustainability 13, no. 20: 11372.
https://doi.org/10.3390/su132011372
APA Style
Molero, G. D., Poveda-Reyes, S., Malviya, A. K., GarcĂa-JimĂ©nez, E., Leva, M. C., & Santarremigia, F. E.
(2021). Computational Solutions Based on Bayesian Networks to Hierarchize and to Predict Factors Influencing Gender Fairness in the Transport System: Four Use Cases. Sustainability, 13(20), 11372.
https://doi.org/10.3390/su132011372