thesis.bbl 10 KB

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  1. \newcommand{\etalchar}[1]{$^{#1}$}
  2. \begin{thebibliography}{KSM{\etalchar{+}}21}
  3. % this bibliography is generated by alphadin.bst [8.2] from 2005-12-21
  4. \providecommand{\url}[1]{\texttt{#1}}
  5. \expandafter\ifx\csname urlstyle\endcsname\relax
  6. \providecommand{\doi}[1]{doi: #1}\else
  7. \providecommand{\doi}{doi: \begingroup \urlstyle{rm}\Url}\fi
  8. \bibitem[And91]{Anderson1991}
  9. \textsc{Anderson}, Robert~M. Roy Malcolm;~May~M. Roy Malcolm;~May:
  10. \newblock \emph{Infectious diseases of humans : dynamics and control}.
  11. \newblock Oxford University Press, 1991
  12. \bibitem[BE22]{Berkhahn2022}
  13. \textsc{Berkhahn}, Sarah ; \textsc{Ehrhardt}, Matthias:
  14. \newblock A physics-informed neural network to model COVID-19 infection and
  15. hospitalization scenarios.
  16. \newblock {In: }\emph{Advances in Continuous and Discrete Models} 2022 (2022),
  17. Oktober, Nr. 1.
  18. \newblock \url{http://dx.doi.org/10.1186/s13662-022-03733-5}. --
  19. \newblock DOI 10.1186/s13662--022--03733--5. --
  20. \newblock ISSN 2731--4235
  21. \bibitem[CD96]{Cooke1996}
  22. \textsc{Cooke}, K.~L. ; \textsc{Driessche}, P. van~d.:
  23. \newblock Analysis of an SEIRS epidemic model with two delays.
  24. \newblock {In: }\emph{Journal of Mathematical Biology} 35 (1996), Dezember, Nr.
  25. 2, S. 240--260.
  26. \newblock \url{http://dx.doi.org/10.1007/s002850050051}. --
  27. \newblock DOI 10.1007/s002850050051. --
  28. \newblock ISSN 1432--1416
  29. \bibitem[DD22]{Doerre2022}
  30. \textsc{Doerre}, Achim ; \textsc{Doblhammer}, Gabriele:
  31. \newblock The influence of gender on COVID-19 infections and mortality in
  32. Germany: Insights from age- and gender-specific modeling of contact rates,
  33. infections, and deaths in the early phase of the pandemic.
  34. \newblock {In: }\emph{PLOS ONE} 17 (2022), Mai, Nr. 5, S. e0268119.
  35. \newblock \url{http://dx.doi.org/10.1371/journal.pone.0268119}. --
  36. \newblock DOI 10.1371/journal.pone.0268119. --
  37. \newblock ISSN 1932--6203
  38. \bibitem[Dem21]{Demtroeder2021}
  39. \textsc{Demtröder}, Wolfgang:
  40. \newblock \emph{Lehrbuch}. Bd.~1: {\emph{Experimentalphysik 1}}.
  41. \newblock 9. Auflage.
  42. \newblock Berlin : Springer Spektrum, 2021. --
  43. \newblock ISBN 978--3--662--62727--3. --
  44. \newblock Auf dem Umschlag: Mit über 2,5 h Lösungsvideos zu ausgewählten
  45. Aufgaben
  46. \bibitem[EK05]{EdelsteinKeshet2005}
  47. \textsc{Edelstein-Keshet}, Leah:
  48. \newblock \emph{Mathematical Models in Biology}.
  49. \newblock Society for Industrial and Applied Mathematics, 2005
  50. \bibitem[GBC16]{Goodfellow-et-al-2016}
  51. \textsc{Goodfellow}, Ian ; \textsc{Bengio}, Yoshua ; \textsc{Courville},
  52. Aaron:
  53. \newblock \emph{Deep Learning}.
  54. \newblock MIT Press, 2016. --
  55. \newblock \url{http://www.deeplearningbook.org}
  56. \bibitem[Gil10]{Gilbert2010}
  57. \textsc{Gilbert}, G.~N.:
  58. \newblock \emph{Agent-based models}.
  59. \newblock 3. pr.
  60. \newblock Los Angeles [u.a.] : Sage Publ., 2010 (Quantitative applications in
  61. the social sciences 153). --
  62. \newblock ISBN 978--1--4129--4964--4
  63. \bibitem[HSW89]{Hornik1989}
  64. \textsc{Hornik}, Kurt ; \textsc{Stinchcombe}, Maxwell ; \textsc{White},
  65. Halbert:
  66. \newblock Multilayer feedforward networks are universal approximators.
  67. \newblock {In: }\emph{Neural Networks} 2 (1989), Januar, Nr. 5, S. 359--366.
  68. \newblock \url{http://dx.doi.org/10.1016/0893-6080(89)90020-8}. --
  69. \newblock DOI 10.1016/0893--6080(89)90020--8. --
  70. \newblock ISSN 0893--6080
  71. \bibitem[KM27]{1927}
  72. \textsc{Kermack}, William~O. ; \textsc{McKendrick}, A.~G.:
  73. \newblock A contribution to the mathematical theory of epidemics.
  74. \newblock {In: }\emph{Proceedings of the Royal Society of London. Series A,
  75. Containing Papers of a Mathematical and Physical Character} 115 (1927),
  76. August, Nr. 772, S. 700--721.
  77. \newblock \url{http://dx.doi.org/10.1098/rspa.1927.0118}. --
  78. \newblock DOI 10.1098/rspa.1927.0118. --
  79. \newblock ISSN 2053--9150
  80. \bibitem[KSM{\etalchar{+}}21]{Kerr2021}
  81. \textsc{Kerr}, Cliff~C. ; \textsc{Stuart}, Robyn~M. ; \textsc{Mistry}, Dina ;
  82. \textsc{Abeysuriya}, Romesh~G. ; \textsc{Rosenfeld}, Katherine ;
  83. \textsc{Hart}, Gregory~R. ; \textsc{Núñez}, Rafael~C. ; \textsc{Cohen},
  84. Jamie~A. ; \textsc{Selvaraj}, Prashanth ; \textsc{Hagedorn}, Brittany ;
  85. \textsc{George}, Lauren ; \textsc{Jastrzębski}, Michał ; \textsc{Izzo},
  86. Amanda~S. ; \textsc{Fowler}, Greer ; \textsc{Palmer}, Anna ;
  87. \textsc{Delport}, Dominic ; \textsc{Scott}, Nick ; \textsc{Kelly}, Sherrie~L.
  88. ; \textsc{Bennette}, Caroline~S. ; \textsc{Wagner}, Bradley~G. ;
  89. \textsc{Chang}, Stewart~T. ; \textsc{Oron}, Assaf~P. ; \textsc{Wenger},
  90. Edward~A. ; \textsc{Panovska-Griffiths}, Jasmina ; \textsc{Famulare}, Michael
  91. ; \textsc{Klein}, Daniel~J.:
  92. \newblock Covasim: An agent-based model of COVID-19 dynamics and interventions.
  93. \newblock {In: }\emph{PLOS Computational Biology} 17 (2021), Juli, Nr. 7, S.
  94. e1009149.
  95. \newblock \url{http://dx.doi.org/10.1371/journal.pcbi.1009149}. --
  96. \newblock DOI 10.1371/journal.pcbi.1009149. --
  97. \newblock ISSN 1553--7358
  98. \bibitem[LLF97]{Lagaris1997}
  99. \textsc{Lagaris}, I.~E. ; \textsc{Likas}, A. ; \textsc{Fotiadis}, D.~I.:
  100. \newblock Artificial Neural Networks for Solving Ordinary and Partial
  101. Differential Equations.
  102. \newblock (1997).
  103. \newblock \url{http://dx.doi.org/10.48550/ARXIV.PHYSICS/9705023}. --
  104. \newblock DOI 10.48550/ARXIV.PHYSICS/9705023
  105. \bibitem[LS12]{Liu2012}
  106. \textsc{Liu}, Xinzhi ; \textsc{Stechlinski}, Peter:
  107. \newblock Infectious disease models with time-varying parameters and general
  108. nonlinear incidence rate.
  109. \newblock {In: }\emph{Applied Mathematical Modelling} 36 (2012), Mai, Nr. 5, S.
  110. 1974--1994.
  111. \newblock \url{http://dx.doi.org/10.1016/j.apm.2011.08.019}. --
  112. \newblock DOI 10.1016/j.apm.2011.08.019. --
  113. \newblock ISSN 0307--904X
  114. \bibitem[Mat84]{Matsumoto1984}
  115. \textsc{Matsumoto}, T.:
  116. \newblock A chaotic attractor from Chua’s circuit.
  117. \newblock {In: }\emph{IEEE Transactions on Circuits and Systems} 31 (1984),
  118. Dezember, Nr. 12, S. 1055--1058.
  119. \newblock \url{http://dx.doi.org/10.1109/tcs.1984.1085459}. --
  120. \newblock DOI 10.1109/tcs.1984.1085459. --
  121. \newblock ISSN 0098--4094
  122. \bibitem[MP72]{Minsky1972}
  123. \textsc{Minsky}, Marvin ; \textsc{Papert}, Seymour~A.:
  124. \newblock \emph{Perceptrons}.
  125. \newblock 2. print. with corr.
  126. \newblock Cambridge/Mass. [u.a.] : The MIT Press, 1972. --
  127. \newblock ISBN 9780262630221. --
  128. \newblock Literaturangaben
  129. \bibitem[MPF23]{Millevoi2023}
  130. \textsc{Millevoi}, Caterina ; \textsc{Pasetto}, Damiano ; \textsc{Ferronato},
  131. Massimiliano:
  132. \newblock A Physics-Informed Neural Network approach for compartmental
  133. epidemiological models.
  134. \newblock (2023).
  135. \newblock \url{http://dx.doi.org/10.48550/ARXIV.2311.09944}. --
  136. \newblock DOI 10.48550/ARXIV.2311.09944
  137. \bibitem[MZ20]{Maziarz2020}
  138. \textsc{Maziarz}, Mariusz ; \textsc{Zach}, Martin:
  139. \newblock Agent‐based modelling for SARS‐CoV‐2 epidemic prediction and
  140. intervention assessment: A methodological appraisal.
  141. \newblock {In: }\emph{Journal of Evaluation in Clinical Practice} 26 (2020),
  142. August, Nr. 5, S. 1352--1360.
  143. \newblock \url{http://dx.doi.org/10.1111/jep.13459}. --
  144. \newblock DOI 10.1111/jep.13459. --
  145. \newblock ISSN 1365--2753
  146. \bibitem[OKF21]{Olumoyin2021}
  147. \textsc{Olumoyin}, K.~D. ; \textsc{Khaliq}, A. Q.~M. ; \textsc{Furati}, K.~M.:
  148. \newblock Data-Driven Deep-Learning Algorithm for Asymptomatic COVID-19 Model
  149. with Varying Mitigation Measures and Transmission Rate.
  150. \newblock {In: }\emph{Epidemiologia} 2 (2021), September, Nr. 4, S. 471--489.
  151. \newblock \url{http://dx.doi.org/10.3390/epidemiologia2040033}. --
  152. \newblock DOI 10.3390/epidemiologia2040033. --
  153. \newblock ISSN 2673--3986
  154. \bibitem[Oks00]{Oksendal2000}
  155. \textsc{Oksendal}, Bernt:
  156. \newblock \emph{Stochastic Differential Equations}.
  157. \newblock 5th ed.
  158. \newblock Berlin, Heidelberg : Springer Berlin / Heidelberg, 2000 (Universitext
  159. Ser.). --
  160. \newblock ISBN 3--540--63720--6. --
  161. \newblock Description based on publisher supplied metadata and other sources.
  162. \bibitem[RHW86]{Rumelhart1986}
  163. \textsc{Rumelhart}, David~E. ; \textsc{Hinton}, Geoffrey~E. ;
  164. \textsc{Williams}, Ronald~J.:
  165. \newblock Learning representations by back-propagating errors.
  166. \newblock {In: }\emph{Nature} 323 (1986), Oktober, Nr. 6088, S. 533--536.
  167. \newblock \url{http://dx.doi.org/10.1038/323533a0}. --
  168. \newblock DOI 10.1038/323533a0. --
  169. \newblock ISSN 1476--4687
  170. \bibitem[Ros58]{Rosenblatt1958}
  171. \textsc{Rosenblatt}, F.:
  172. \newblock The perceptron: A probabilistic model for information storage and
  173. organization in the brain.
  174. \newblock {In: }\emph{Psychological Review} 65 (1958), Nr. 6, S. 386--408.
  175. \newblock \url{http://dx.doi.org/10.1037/h0042519}. --
  176. \newblock DOI 10.1037/h0042519. --
  177. \newblock ISSN 0033--295X
  178. \bibitem[RPK17]{Raissi2017}
  179. \textsc{Raissi}, Maziar ; \textsc{Perdikaris}, Paris ; \textsc{Karniadakis},
  180. George~E.:
  181. \newblock \emph{Physics Informed Deep Learning (Part I): Data-driven Solutions
  182. of Nonlinear Partial Differential Equations}
  183. \bibitem[Rud07]{Rudin2007}
  184. \textsc{Rudin}, Walter:
  185. \newblock \emph{Analysis}.
  186. \newblock Oldenbourg Wissenschaftsverlag GmbH, 2007
  187. \bibitem[Sch26]{Schroedinger1926}
  188. \textsc{Schrödinger}, E.:
  189. \newblock An Undulatory Theory of the Mechanics of Atoms and Molecules.
  190. \newblock {In: }\emph{Physical Review} 28 (1926), Dezember, Nr. 6, S.
  191. 1049--1070.
  192. \newblock \url{http://dx.doi.org/10.1103/physrev.28.1049}. --
  193. \newblock DOI 10.1103/physrev.28.1049. --
  194. \newblock ISSN 0031--899X
  195. \bibitem[SdC17]{Smirnova2017}
  196. \textsc{Smirnova}, Alexandra ; \textsc{deCamp}, Linda ; \textsc{Chowell},
  197. Gerardo:
  198. \newblock Forecasting Epidemics Through Nonparametric Estimation of
  199. Time-Dependent Transmission Rates Using the SEIR Model.
  200. \newblock {In: }\emph{Bulletin of Mathematical Biology} 81 (2017), Mai, Nr. 11,
  201. S. 4343--4365.
  202. \newblock \url{http://dx.doi.org/10.1007/s11538-017-0284-3}. --
  203. \newblock DOI 10.1007/s11538--017--0284--3. --
  204. \newblock ISSN 1522--9602
  205. \bibitem[SH23]{Setianto2023}
  206. \textsc{Setianto}, Setianto ; \textsc{Hidayat}, Darmawan:
  207. \newblock Modeling the time-dependent transmission rate using gaussian pulses
  208. for analyzing the COVID-19 outbreaks in the world.
  209. \newblock {In: }\emph{Scientific Reports} 13 (2023), M{\^^b a}rz, Nr. 1.
  210. \newblock \url{http://dx.doi.org/10.1038/s41598-023-31714-5}. --
  211. \newblock DOI 10.1038/s41598--023--31714--5. --
  212. \newblock ISSN 2045--2322
  213. \bibitem[SRS21]{Shaier2021}
  214. \textsc{Shaier}, Sagi ; \textsc{Raissi}, Maziar ; \textsc{Seshaiyer},
  215. Padmanabhan:
  216. \newblock \emph{Data-driven approaches for predicting spread of infectious
  217. diseases through DINNs: Disease Informed Neural Networks}
  218. \bibitem[TP85]{Tenenbaum1985}
  219. \textsc{Tenenbaum}, Morris ; \textsc{Pollard}, Harry:
  220. \newblock \emph{Ordinary Differential Equations}.
  221. \newblock Harper and Row, Publishers, Inc., 1985
  222. \end{thebibliography}