Simulation & Prescriptive Analytics – References

  1. Diappi L., Buscema P.M., Ottanà M., Complexity in Sustainability: an Investigation of the Italian Urban System through Self-Reflexive Neural Networks, in Diappi L. (ed) “Evolving cities” , Ashgate Publishing, England, 2004.
  2. Buscema P.M., Terzi S., Maurelli G., Capriotti M., V. Carlei, The Smart Library Architecture of an Orientation Portal, DOI 10.1007/s11135-005-1081-x Quality & Quantity (2006) 40:911–933.
  3. Buscema P.M., Newman F. , Grossi E., Tastle W., Application of adaptive systems methodology to radiotherapy, Fuzzy Information Processing Society (NAFIPS), 2010 Annual Meeting of the North American, 12-14 July 2010, Toronto, ON, 12-14 July 2010, IEEE, DOI: 10.1109/NAFIPS.2010.5548297.
  4. Street M., et al. Artificial Neural Networks, and Evolutionary algorithms as a Systems biology approach to a data-base on fetal growth restriction. Progress in biophysics and molecular biology (2013).
  5. Buscema P.M., Street M., Grossi E., Data Mining Of Determinants Of Intrauterine Growth Retardation Revisited Using Novel Algorithms Generating Semantic Maps And Prototypical Discriminating Variable Profiles, PLOS ONE | DOI:10.1371/journal.pone.0126020 July 9, 2015.
  6. Buscema P.M., Tastle W. J., Artificial Neural Network. What-If Theory. International Journal of Information Systems and Social Change, 6(4), 52-81, October-December 2015. July 2015
  7. Buscema P.M., Maurelli G., Mennini F.S., Gitto L., Russo S., Ruggeri M., Coretti S., Cicchetti A., Artificial neural networks and their potentialities in analyzing budget health data: an application for Italy of what-if theory. Quality & Quantity, 10.1007/s11135-016-0329-y, March 2016.
  8. Buscema P.M., Ferilli G., Sacco P.L., What kind of ‘world order’? An artificial neural networks approach to intensive data mining, Technological Forecasting & Social Change 117 (2017) 46–56