Add deep feedforward networks to State of the Art

assets/bibliography.bib

@@ -1371,3 +1371,52 @@
   url             = {http://dx.doi.org/10.1080/713827180},
   publisher       = {Informa UK Limited}
 }
+
+@Article{Lopez_Moreno_2016,
+  author          = {Lopez-Moreno, Ignacio and Gonzalez-Dominguez, Javier and
+                  Martinez, David and Plchot, Oldřich and Gonzalez-Rodriguez,
+                  Joaquin and Moreno, Pedro J.},
+  title           = {On the use of deep feedforward neural networks for
+                  automatic language identification},
+  journal         = {Computer Speech & Language},
+  year            = 2016,
+  volume          = 40,
+  month           = {Nov},
+  pages           = {46–59},
+  issn            = {0885-2308},
+  doi             = {10.1016/j.csl.2016.03.001},
+  url             = {http://dx.doi.org/10.1016/j.csl.2016.03.001},
+  publisher       = {Elsevier BV}
+}
+
+@Article{Chakraborty_2020,
+  author          = {Chakraborty, Sourav and Choudhary, Arun Kumar and Sarma,
+                  Mausumi and Hazarika, Manuj Kumar},
+  title           = {Reaction order and neural network approaches for the
+                  simulation of COVID-19 spreading kinetic in India},
+  journal         = {Infectious Disease Modelling},
+  year            = 2020,
+  volume          = 5,
+  pages           = {737–747},
+  issn            = {2468-0427},
+  doi             = {10.1016/j.idm.2020.09.002},
+  url             = {http://dx.doi.org/10.1016/j.idm.2020.09.002},
+  publisher       = {Elsevier BV}
+}
+
+@Article{Mansoor_2021,
+  author          = {Mansoor, Muhammad and Grimaccia, Francesco and Leva, Sonia
+                  and Mussetta, Marco},
+  title           = {Comparison of echo state network and feed-forward neural
+                  networks in electrical load forecasting for demand response
+                  programs},
+  journal         = {Mathematics and Computers in Simulation},
+  year            = 2021,
+  volume          = 184,
+  month           = {Jun},
+  pages           = {282–293},
+  issn            = {0378-4754},
+  doi             = {10.1016/j.matcom.2020.07.011},
+  url             = {http://dx.doi.org/10.1016/j.matcom.2020.07.011},
+  publisher       = {Elsevier BV}
+}