Since Bayesian network (BN) was introduced in the field of artificial intelligence in 1980s, a number of inference algorithms have been developed for probabilistic reasoning. Ho...
Abstract. Research collaborations are always encouraged, as they often yield good results. However, the researcher network contains massive amounts of experts in various discipline...
We introduce a polynomial-time algorithm to learn Bayesian networks whose structure is restricted to nodes with in-degree at most k and to edges consistent with the optimal branch...
This paper presents a genetic algorithm (GA) with specialized encoding, initialization and local search genetic operators to optimize communication network topologies. This NPhard...
Traditional methods of dealing with variability in simulation input data are mainly stochastic. This is most often the best method to use if the factors affecting the variation or...