A Knowledge Innovation Algorithm Based on Granularity


  •  yan taishan    

Abstract

The structure of Human knowledge is regarded as granule state by rough sets theory. Granularity is used to denote this structure of knowledge. Knowledge itself evolves ceaselessly as creatures. Knowledge innovation is an important step of knowledge evolution course. Based on knowledge granularity, a knowledge innovation method was proposed in this paper. The main idea of this method is to constitute the partition granularity of knowledge base space ceaselessly depend on the measure consistency of attribute, till the sort of every granules in the granularity is only one. There is only one computation namely the measure consistency of attribute in the algorithm, so the numerical calculation work is little, the time complexity is low, and the algorithm is feasible absolutely. Experiments were taken on the imperfect knowledge base space of day weather classification by this algorithm, its working course was explained. The successful results show that this algorithm is correct and valid.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • Issn(Print): 1913-8989
  • Issn(Onlne): 1913-8997
  • Started: 2008
  • Frequency: quarterly

Journal Metrics

(The data was calculated based on Google Scholar Citations)

Google-based Impact Factor (2018): 18.20

h-index (January 2018): 23

i10-index (January 2018): 90

h5-index (January 2018): 11

h5-median(January 2018):17

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