Abstract
The existing evaluation methods of patent quality take expert scoring as the principal thing. Each expert is required to score all the indexes and to assign the corresponding weight according to the relative importance of the index. But index system generally involves multiple indicators in different fields. Experts can not make accurate evaluation of indicators beyond their research fields, and fuzzy indicators also make experts hesitate and wander between several evaluation values. Hesitant fuzzy soft sets can more accurately describe the fuzzy nature of things, have no restrictions on optional objects, and take full account of the degree of hesitation of expert decision making. Accordingly, this paper proposes a evaluation model of patent quality based on hesitant fuzzy soft sets and gives specific evaluation steps.
Funded projects: 1. A quality monitoring economic model based on feedforward adjustment and its performance evaluation (172102210078); 2. Economic model of self correlation process quality monitoring and its performance evaluation (17A630069); 3. Multiple objective optimization design based on the economic statistics of PLD process quality control (71672209); 4. The smart phone surface of defect monitoring and real time quality diagnosis of manufacturing process (U1604262).
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Zhang, L., Li, Q., Yu, Jl. (2019). Patent Quality Evaluation Model Based on Hesitant Fuzzy Soft Set. In: Huang, G., Chien, CF., Dou, R. (eds) Proceeding of the 24th International Conference on Industrial Engineering and Engineering Management 2018. Springer, Singapore. https://doi.org/10.1007/978-981-13-3402-3_65
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