Mobile crowd sensing user income selection method
A mobile crowd sensing and user technology, applied in data processing applications, complex mathematical operations, instruments, etc., can solve the problems of reducing the accuracy of the optimal profit strategy selection method and the actual guiding value
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Embodiment 1
[0055] The purpose of the present invention can be achieved through the following technical solutions:
[0056] A method for selecting mobile crowd sensing user revenue based on data quality assessment and evolutionary game, said method comprising the following steps:
[0057] The first step is to build the publisher-user evolutionary game model, which is defined as a quadruple, and the details are as follows:
[0058] 1) N=(N u ,N p ) represents both players in the evolutionary game, where N u means user, N p Indicates the publisher;
[0059] 2) W=(uw,pw) represents the choice of the strategies of both players in the game, where uw={uw 1 ,uw 2 ,...,uw n} represents the user's policy set, that is, the set of user data quality, pw={pw 1 ,pw 2 ,...,pw m} represents the strategy set of the publisher, that is, the task incentive set;
[0060] 3) R=(d,q) represents the set of strategy selection probabilities of both parties in the game, where d i Indicates that the publ...
Embodiment 2
[0116] The invention is applicable to the mobile crowd sensing revenue selection method that fully considers the user data quality. The invention models the entire mobile group intelligence sensing process as a publisher-user evolutionary game model, and evaluates the quality of user data therein. The design of various existing mobile crowd sensing revenue selection methods ignores the quality of data submitted by users, and most of the research on revenue games is based on individual rationality, which leads to the failure of user revenue to meet expectations. Based on this, the present invention first models the selection of the benefits of both parties as a publisher-user evolutionary game model; then, calculates the deviation degree of data quality according to the relevant attributes of the user uploaded data, and removes low-quality user data; The user solves the evolutionary strategy solution and conducts stability analysis to obtain the user's optimal profit strategy u...
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