Study on evaluation standard of uncertainty of design wave height calculation model

The accurate calculation of marine environmental design parameters depends on the probability distribution model,and the calculation results of different distribution models are often different.It is very important to determine which distribution model is more stable and reasonable when extrapolating the recurrence level of the studied sea area.In this paper,we constructed an evaluation method of the overall uncertainty of the calculation results and a measurement of the uncertainty of the design parameters derivation model,by incorporating the influence of sample information on the model information entropy,such as sample size,degree of dispersion,and sampling error.Results show that the sample data size and the degree of dispersion are directly proportional to the information entropy.Within the same group of data,the maximum entropy distribution model has the lowest overall uncertainty,while the Gumbel distribution model has the largest overall uncertainty.In other words,the maximum entropy distribution model has good applicability in the accurate calculation of marine environmental design parameters.

Seed Selection for Data Offloading Based on Social and Interest Graphs

The explosive growth of mobile data demand is becoming an increasing burden on current cellular network.To address this issue,we propose a solution of opportunistic data offloading for alleviating overloaded cellular traffic.The principle behind it is to select a few important users as seeds for data sharing.The three critical steps are detailed as follows.We first explore individual interests of users by the construction of user profiles,on which an interest graph is built by Gaussian graphical modeling.We then apply the extreme value theory to threshold the encounter duration of user pairs.So,a contact graph is generated to indicate the social relationships of users.Moreover,a contact-interest graph is developed on the basis of the social ties and individual interests of users.Corresponding on different graphs,three strategies are finally proposed for seed selection in an aim to maximize overloaded cellular data.We evaluate the performance of our algorithms by the trace data of real-word mobility.It demonstrates the effectiveness of the strategy of taking social relationships and individual interests into account.