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This paper introduces an improved particle swarm optimization (PSO) as a new tool for training an artificial neural network (ANN). As a consequence, an accurate comparison with other optimization methods is needed; the typical supervised feed-forward backpropagation algorithm (EBP) and the classical genetic algorithm (GA) are chosen. The aim is to highlight(More)
—In this paper, a modified Bayesian Optimization Algorithm (BOA), named M-BOA, is proposed to introduce a suitable mutation scheme for the traditional procedure in order to speed up the convergence of the algorithm and to avoid it to be trapped in local minima or to stagnate in suboptimal solutions. The proposed algorithm has been applied both to a specific(More)
This paper aims to optimize the design of a novel antenna for aerospace applications to be integrated on an experimental rocket that has been designed in an advanced research student program. In order to optimize EM performance of such a system a novel optimization algorithm called SNO, Social Network Optimization, has been developed and tested to find the(More)
Bone mineral content (BMC) and testosterone levels were evaluated and compared in 10 hypogonadal males and 10 normal, age-matched controls. In 6 of the subjects an investigation was also carried out into the effects of testosterone administration on lumbar BMC, calcitonin (CT) response to hypercalcaemia, osteocalcin (BGP) and the fasting urinary(More)
Double photon absorptiometry comparison was done of lumbar bone mineral content (BMC) values in 40 women with well-compensated non-insulin-dependent diabetes mellitus (type II) and on dietary and/or oral hypoglycemic treatment, and 35 age-matched non-diabetic women, to determine the presence and degree of osteoporosis in this type of diabetes by means of a(More)
A new hybrid evolutionary algorithm called GSO (genetical swarm optimization) Is here presented. GSO combines the well known particle swarm optimization and genetic algorithms. The GSO algorithm is essentially a population-based heuristic search technique which can be used to solve combinatorial optimization problems, modeled on the concept of natural(More)
—In this paper a new class of hybridization strategies between GA and PSO is presented and validated. The Genetical Swarm Optimization (GSO) approach is presented here with respect with different test cases to prove its effectiveness. GSO is a hybrid evolutionary technique developed in order to exploit in the most effective way the uniqueness and(More)