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    • UNIR REVISTAS
    • Revista IJIMAI
    • 2014
    • vol. 2, nº 6, june 2014
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    • UNIR REVISTAS
    • Revista IJIMAI
    • 2014
    • vol. 2, nº 6, june 2014
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    Business and Social Behaviour Intelligence Analysis Using PSO

    Autor: 
    Bhaskar, Vinay S
    ;
    Kumar Singh, Abhishek
    ;
    Dhruw, Jyoti
    ;
    Parashar, Anubha
    ;
    Sharma, Mradula
    Fecha: 
    06/2014
    Palabra clave: 
    artificial intelligence; geographic information system; optimization; PSO; IJIMAI
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/9776
    DOI: 
    http://dx.doi.org/10.9781/ijimai.2014.268
    Dirección web: 
    https://www.ijimai.org/journal/node/626
    Open Access
    Resumen:
    The goal of this paper is to elaborate swarm intelligence for business intelligence decision making and the business rules management improvement. The paper introduces the decision making model which is based on the application of Artificial Neural Networks (ANNs) and Particle Swarm Optimization (PSO) algorithm. Essentially the business spatial data illustrate the group behaviors. The swarm optimization, which is highly influenced by the behavior of creature, performs in group. The Spatial data is defined as data that is represented by 2D or 3D images. SQL Server supports only 2D images till now. As we know that location is an essential part of any organizational data as well as business data: enterprises maintain customer address lists, own property, ship goods from and to warehouses, manage transport flows among their workforce, and perform many other activities. By means to say a lot of spatial data is used and processed by enterprises, organizations and other bodies in order to make the things more visible and self-descriptive. From the experiments, we found that PSO is can facilitate the intelligence in social and business behaviour.
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    Nombre: ijimai20142_6_8_pdf_20898.pdf
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