Research Article
Supporting Business Privacy Protection in Wireless Sensor Networks
Algorithm 1
The ACO-based algorithm for learning the BN structure.
Input: Set of all/candidate edges | Output: Bayesian network | //Initialization | () define m as the number of ants; | () pheromones : initialize each entry of with ; | () define as max number of iterations; | () ; | () = empty graph; | //Optimization | () repeat | () for to do | () for to do ; | () for and to do | () if () then ; | () end | () repeat | () Select two indexes and by using (5) and (6) and assign edge to ; | () if () then ; | () ; | () for all and do | ; | () for to do | () if () then ; | () end | () ; | () until ; | () end | () ; | () if then ; | () Update pheromone according to (3) using ; | () ; | () until ; | () return Bayesian network with structure |
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