This paper proposes a novel recombination scheme for evolutionary algorithms, which can guide the new population generation towards the maximum increase of the objective function....
Despite the advances in software engineering since 1968, current methods for going from a set of functional requirements to a design are not as direct, repeatable and constructive...
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...
Abstract. This paper proposes a new learning method for process neural networks (PNNs) based on the Gaussian mixture functions and particle swarm optimization (PSO), called PSO-LM....
The greatest impediment to practical adoption of iterative methods for X-ray CT is the computation burden of cone-beam forward and back-projectors. Moreover, forward and back-proje...