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A new framework for the complex system’s simulation and analysis

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Abstract

Statistics (or probabilistic theory) and machine learning are currently the main methods of complex system researching. In order to solve the problems of the statistics and machine learning the CUP algorithm in this paper is proposed. The paper gave the basic definition and the measure of the CUP meanwhile it provided the theoretical support for application. Fitting algorithm based on CUP system was introduced. The algorithm can output more information from the fitting process. Contract of fitting to Lorenz system between CUP algorithm and artificial neural net was displayed in the following part. The different fitting effect by different candidate coefficient set is discussed. A typical example of realistic social application and other usages are put up. The CUP algorithm provides the probability and numerical fitting conclusion CUP algorithm the same time while numerical calculation accuracy is optional for different problems.

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Authors and Affiliations

  1. School of Computer Engineering and Science, Shanghai University, Shanghai, China

    Yuan Gao & Qing Li

Authors
  1. Yuan Gao
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  2. Qing Li
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Correspondence to Yuan Gao.

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Gao, Y., Li, Q. A new framework for the complex system’s simulation and analysis. Cluster Comput 22 (Suppl 4), 9097–9104 (2019). https://doi.org/10.1007/s10586-018-2071-9

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  • DOI: https://doi.org/10.1007/s10586-018-2071-9

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