• DocumentCode
    245792
  • Title

    Power-Activated WASD Neuronet Based Russian Population Estimation, Correction, and Prediction

  • Author

    Yunong Zhang ; Jianxi Liu ; Dongsheng Guo ; Sitong Ding ; Hongzhou Tan

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Sun Yat-sen Univ. (SYSU), Guangzhou, China
  • fYear
    2014
  • fDate
    19-21 Dec. 2014
  • Firstpage
    1232
  • Lastpage
    1236
  • Abstract
    In recent years, the serious situation of Russian population causes concerns of the government, which also attracts great attentions of researchers from all over the world. The research on Russian population can help the government to make positive policies for solving the crisis and boosting economic growth. In this paper, implicitly considering almost all factors that influence population development, we present a 3-layer feed forward power-activated neuronet (PAN) equipped with the weights-and-structure-determination (WASD) algorithm for the estimation, correction and prediction of Russian population. Many numerical tests are conducted via WASD-PAN using past 2013-year Russian population data. We estimate the Russian population from 1000AD to 1800AD, correct it around 1897AD, and further indicate several possibilities of Russian population in the future. With the most possibility, Russian population is predicted to decrease steadily in next decade, while it is still possible that Russian population will (finally) increase.
  • Keywords
    feedforward neural nets; numerical analysis; social sciences; 3-layer feedforward power-activated neuronet; PAN; Russian population correction; Russian population estimation; Russian population prediction; economic growth; numerical tests; power-activated WASD neuronet; weights-and-structure-determination algorithm; Data models; Educational institutions; Estimation; Market research; Neurons; Sociology; Statistics; Power-activated neuronet (PAN); Russian population; correction; prediction; weights-and-structure-determination algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4799-7980-6
  • Type

    conf

  • DOI
    10.1109/CSE.2014.238
  • Filename
    7023748