期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2016
卷号：7
期号：4
DOI：10.14569/IJACSA.2016.070407
出版社：Science and Information Society (SAI)
摘要：To explore new system self-organizing theory, it’s urgent to find a new method in the system science. This paper combines factor space theory with system non-optimum theory, applies it into the research of system self-organizing theory and proposes new concepts as system factor space, object-factor and space-order relation. It constructs factor-space framework of system self-organizing based on factor mapping and object inversion, studies system ordering from a new perspective with optimum and non-optimum attributes as the basis of system uncertainty, and expands factor space theory from f(0,o) to f(o,0). The research suggests that the construction of system factor space is to build an information system capable of self-learning for system self-organization and better enhance functions of system self-organization by adopting information fusion of data analysis and perception judgment.
