An alternative measure: Chinese urbanization

Xu Bing, Junzo Watada

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Using the nonparametric investment weighted kernel density approach, the study presents an alternative measure on Chinese urbanization distribution, which takes a new perspective on how investment promoting urbanization. It proposes projects to promote urbanization as an application. The projects illustrate that the overall urbanization can be promoted by 2 percent if make a 10 percent rise of investment put into the cities with urbanization levels higher than the average level; the same effect can be gained without any additional investment by changing 50 percent of the original added value of investment in the cities.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Pages333-341
    Number of pages9
    Volume4694 LNAI
    EditionPART 3
    Publication statusPublished - 2007
    Event11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007 - Vietri sul Mare
    Duration: 2007 Sep 122007 Sep 14

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 3
    Volume4694 LNAI
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007
    CityVietri sul Mare
    Period07/9/1207/9/14

    Keywords

    • Investment weighted model
    • Measure
    • Projects
    • Urbanization

    ASJC Scopus subject areas

    • Computer Science(all)
    • Biochemistry, Genetics and Molecular Biology(all)
    • Theoretical Computer Science

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