Optimal program slicing determines for a statement S in a program whether or not S affects a specified set of statements, given that all conditionals in are interpreted as non-d...
In solving application problems, the data sets used to train a neural network may not be hundred percent precise but within certain ranges. Representing data sets with intervals, ...
We introduce a new approach to GA (Genetic Algorithms) based problem solving. Earlier GAs did not contain local search (i.e. hill climbing) mechanisms, which led to optimization d...
Hitoshi Iba, Tetsuya Higuchi, Hugo de Garis, Taisu...
— Many inference problems that arise in sensor networks require the computation of a global conclusion that is consistent with local information known to each node. A large class...
Simulated annealing (SA) and deterministic continuation are well-known generic approaches to global optimization. Deterministic continuation is computationally attractive but produ...