## 5 Conclusions  
In this study, for investigating the problem of data transmission in opportunistic mobile social networks, we propose and develop an adaptive routing-forwarding control scheme based on fuzzy recognition and decision-making model (FPRDM), which contains three interlocking steps: fuzzy recognition for node classification, weight adjustment for social features, and the inference process for the fuzzy relationship between node profile and data transmission. In an opportunistic mobile social network, message users carrying smart mobile devices randomly move around within a certain communication area, so they could be identified and located by several crucial and representative social attributes. After the social characteristics of mobile users have been formalized from context information to digital eigenvector, the obtained quantization vector is considered as a fuzzy input and will be utilized to determine the corresponding fuzzy subset and membership degree. Based on the training results from the improved AHP testing in a real dataset, the FPRDM approach allocates a suitable weight to each social characteristic of message user and determines three different grades of membership functions (high, medium, and low) for the quantization vector. A high membership degree between two nodes indicates that there is a relatively high social similarity between them and they are more likely to belong to the same online community. On the contrary, a low membership between a pair of message users suggests that they do not communicate with each other frequently and there are fewer opportunities for message routing and forwarding between them. Afterwards, on the basis of the application of a defuzzfier component, the fuzzy relationship between social attribute and node recognition could be translated into a specific transmission priority value, which is regarded as a significant reference for message routing and forwarding in the networks. To evaluate the optimization performance of the FPRDM algorithm, simulation results demonstrate that it dramatically reduces the end-to-end delay and the network overhead, and slightly enhances the delivery ratio as compared with the other four routing strategies.  
In future studies, we will work on the information fusion of more social features of mobile users in OSNs so that some more credible decisions on data dissemination could be provided, and more importantly, constructing an effective routing security protocol for tackling the issue of privacy protection in the data transmission process.  
[PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] conceived the idea of the paper. [PERSON], [PERSON], [PERSON], [PERSON]-S.H., [PERSON] and [PERSON] designed and performed the experiments; [PERSON], [PERSON]-S.H., [PERSON] and [PERSON] analyzed the data; [PERSON]-[PERSON], [PERSON] and [PERSON] contributed reagents/materials/analysis tools; [PERSON] wrote and revised the paper.  
**Funding:** This work is supported by Civil Aircraft Project under Grant No. XJ-2015-D-76, and the major and key project of the Shaanxi Province key research and development plan under Grant No. 2016 MSZD-G-8-1.  
**Conflicts of Interest:** The authors declare that they have no competing interests.