Evaluation of scientific publications with hesitant fuzzy uncertain linguistic and semantic information

Scientific and technological papers play a fundamental role in the scientific and technological innovation of countries. The quality control of scientific and technological articles is vital to the journals and management of personnel. This paper investigates multiple attribute decision-making problems with the application of hesitant fuzzy uncertain linguistic information. Motivated by the ideal traditional I-COA operator, an induced hesitant fuzzy uncertain linguistic correlated averaging (IHFULCA) operator is developed. The IHFULCA operator was used to develop approaches to solve hesitant fuzzy uncertain linguistic multiple attribute decision-making problems. Finally, a practical example for evaluating the academic value of scientific and technological papers is provided to verify the developed approach and demonstrate its practicality and effectiveness.