Genetic_Programming_Theory_and_Practice_XIII

(C. Jardin) #1

260 S. Stijven et al.


Crombecq K, De Tommasi L, Gorissen D, Dhaene T (2009) A novel sequential design strategy
for global surrogate modeling. In: Winter simulation conference, Austin, Texas, WSC ’09,
pp 731–742
Evolved Analytics LLC (2011) DataModeler Release 8.0 Documentation. Evolved Analytics LLC



  • http://www.evolved-analytics.com
    Ferguson N, Cummings D, Cauchemez S, Fraser C, Riley S, Meeyai A, Iamsirithaworn S, Burke
    D (2005) Strategies for containing an emerging influenza pandemic in Southeast Asia. Nature
    437(7056):209–214
    Ferguson N, Cummings D, Fraser C, Cajka J, Cooley P, Burke D (2006) Strategies for mitigating
    an influenza pandemic. Nature 442(7101):448–452
    Germann T, Kadau K, Longini Jr I, Macken C (2006) Mitigation strategies for pandemic influenza
    in the United States. PNAS 103(15):5935–5940
    Halloran M, Ferguson N, Eubank S, Longini I, Cummings D, Lewis B, Xu S, Fraser C, Vullikanti
    A, Germann T, et al (2008) Modeling targeted layered containment of an influenza pandemic
    in the United States. PNAS 105(12):4639–4644
    Husslage B, Rennen G, Van Dam ER, Den Hertog D (2006) Space-filling Latin hypercube designs
    for computer experiments. Tilburg University
    Kordon AK, Smits GF (2001) Soft sensor development using genetic programming. In: Spector L,
    Goodman ED, Wu A, Langdon WB, Voigt HM, Gen M, Sen S, Dorigo M, Pezeshk S, Garzon
    MH, Burke E (eds) Proceedings of the genetic and evolutionary computation conference
    (GECCO-2001), Morgan Kaufmann, San Francisco, California, pp 1346–1351.http://www.
    cs.bham.ac.uk/~wbl/biblio/gecco2001/d24.pdf
    Kordon AK (2012) Applying intelligent systems in industry: a realistic overview. In proceedings
    of the 6th IEEE international conference intelligent systems.http://ieeexplore.ieee.org/xpl/
    articleDetails.jsp?tp=&arnumber=6335108
    Kordon AK (2014) Applying genetic programming in business forecasting. Genetic programming
    theory and practice XI.http://link.springer.com/chapter/10.1007/978-1-4939-0375-7_6
    Ma J, Ackerman E, Yang J (1993) Parameter sensitivity of a model or viral epidemics simulated
    with Monte Carlo techniques. I. illness attack rates. Int J Biomed Comput 32:237–253
    Piedra P, Gaglani M, Kozinetz C, Herschler G, Riggs M, Griffith M, Fewlass C, Watts M, Hessel C,
    Cordova J, et al (2005) Herd immunity in adults against influenza-related illnesses with use of
    the trivalent-live attenuated influenza vaccine (CAIV-T) in children. Vaccine 23(13):1540–1548
    Santner TJ, Williams BJ, Notz WI (2003) The design and analysis of computer experiments.
    Springer, New York
    Smits G, Kotanchek M (2004) Pareto-front exploitation in symbolic regression, Chap. 17
    In: O’Reilly UM, Yu T, Riolo RL, Worzel B (eds) Genetic programming theory and practice II.
    Springer, Ann Arbor, pp 283–299. doi:10.1007/0-387-23254-0_17
    Smits G, Vladislavleva E (2008) Trustable symbolic regression models: using ensembles interval
    arithmetic and pareto fronts to develop robust and trust aware models. In: Dow Benelux
    BV, Terneuzen (eds) Tilburg University, Tilburg, the Netherlands. Evolved-Analytics, LLC,
    Midland, MI, USAhttp://link.springer.com/chapter/10.1007%2F978-0-387-76308-8_12
    Stijven S, Minnebo W, Vladislavleva K (2011) Separating the wheat from the chaff: on feature
    selection and feature importance in regression random forests and symbolic regression. In: Pro-
    ceedings of the 13th annual conference companion on genetic and evolutionary computation,
    Dublin, GECCO ’11, pp 623–630
    Trustable symbolic regression models: using ensembles, interval arithmetic and pareto fronts to
    develop robust and trust-aware models
    Vladislavleva E , Smits G, Kotanchek M (2008) Better solutions faster: soft evolution of robust
    regression models in pareto genetic programming. In: Dow Benelux BV, Terneuzen (eds)
    Tilburg University, Tilburg, the Netherlands. Evolved-Analytics, LLC, Midland, MI, USA
    http://link.springer.com/chapter/10.1007%2F978-0-387-76308-8_2
    Willem L, Stijven S, Vladislavleva E, Broeckhove J, Beutels P, Hens N (2014) Active learning to
    understand infectious disease models and improve policy making. PLoS Comput Biol 10(4).
    doi:10.1371/journal.pcbi.1003563.http://dx.doi.org/10.1371/journal.pcbi.1003563

Free download pdf