An Adaptive Network-Based Fuzzy Inference System to Intellectual Property Risk Assessment in Crowdsourcing Design
Chao Yin, Ligao Pan, Xiaobin Li · 2021
The crowdsourcing design service model provides an effective way for the R&D and innovation of the manufacturing industry and the personalized and service-oriented development of products. Intellectual property is the core resource in the crowdsourcing design service model, which is faced with various risks due to the lack of effective control. In this context, this paper proposes an intellectual property risk assessment method based on an adaptive network-based fuzzy inference system (ANFIS) in crowdsourcing design. First of all, the influencing factors of intellectual property risk in crowdsourcing design are analyzed, and a set of intellectual property risk assessment index system is constructed. Secondly, a risk assessment model based on ANFIS is established to quantitatively assess intellectual property risks in crowdsourcing design. Finally, the proposed ANFIS model has been trained and evaluated, and the experimental results show that the method can achieve accurate evaluation of intellectual property risks.