Evaluation of Academic Level of Sci-tech Journals Based on Rough Set and TOPSIS


  •  Nie He    
  •  Yuan-Biao Zhang    
  •  Zhen Zhang    
  •  Xin-Guang Lv    

Abstract

This paper aims to objectively evaluate the academic level of sci-tech journals, reducing mistakes and random errors caused by human factors in traditional academic evaluation. Evaluation indicators of sci-tech journals are reduced based on equivalence relation thought in Rough set theory, removing the miscellaneous indicators, and form the core evaluation indicator system. By studying the degree of importance of the core evaluation indicators’ attributes to determine the appropriate weight, to avoid interference of human factors in the weight determination, so that the evaluation results of sci-tech journals can be more objective. Combine obtained weight of core evaluation indicators with related data, and using TOPSIS method to make comprehensive evaluation rankings for journals. Finally, using the model to validate data of sci-tech journals, and achieved good results, proved the feasibility and effectiveness of the model.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1927-7032
  • ISSN(Online): 1927-7040
  • Started: 2012
  • Frequency: bimonthly

Journal Metrics

  • h-index (December 2021): 20
  • i10-index (December 2021): 51
  • h5-index (December 2021): N/A
  • h5-median(December 2021): N/A

( The data was calculated based on Google Scholar Citations. Click Here to Learn More. )

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