Study on Optimizing Configuration of Precise Functional Modules for UAV Products Based on Users' Personalized Needs under Big Data

This paper focuses on optimization of the precise configuration of functional modules. Customers usually face difficulties in explaining their personalized requirements clearly as they are lack of professional knowledge. Under the environment of big data, this paper resolves this issue by analyzing the numerous real operating data in order to gain the authentic user needs which may not be discovered in customer investigation. By using fuzzy c-means clustering method to divide the users’ expected functions and performance, the classification of user’s personalized demand can be obtained. The weights of each category of users are then calculated. Finally, the appropriate functional modules that can meet the customer needs well can be acquired. An example of UVA product is also indicated in this paper to prove the effectiveness and efficiency of the proposed model.