... The attenuation parameter, m determines the amount of contribution of the peak value to the global function. For the present study, the value of m was considered as 2 [ 33 ]. A multi-objective GA with constrained handling capability, namely, Nondominated Sorting Genetic Algorithm-II (NSGA-II) was used...

... was devised to produce an FE model of liver tissue. Material constants were identified by a genetic algorithm applied to the experimental results of unconfined compressions of bovine liver. The approach for SPS involves B-spline interpolations of sample data generated from the FE model of liver. Two...

...Hing Wah Lee; Parthiban Arunasalam; William P. Laratta; Kankanhalli N. Seetharamu; Ishak A. Azid In this study, a hybridized neuro-genetic optimization methodology realized by embedding finite element analysis (FEA) trained artificial neural networks (ANN) into genetic algorithms (GA), is used...

... distribution on the surface was imaged using an infrared camera. In order to estimate the location and heat generation rate of the source from these temperature distributions, a genetic algorithm was used as the estimation method. The genetic algorithm utilizes a finite difference scheme for the direct...

...) and a genetic algorithm (GA) optimizing method. The average initial shear modulus of brainstem matrix of 4-week old pigs was 12.7 Pa , and therefore the brainstem offers little resistance to large shear deformations in the parallel or perpendicular directions, due to the dominant contribution of the matrix...

... and thickness of the cartilage layer. In this study, we developed a micro-indentation testing system to determine the compressive and biphasic mechanical properties of cartilage in the small joints of the mouse. A nonlinear optimization program employing a genetic algorithm for parameter estimation, combined...

... and verified using a biomechanical test problem. For comparison, all test problems were also solved with three off-the-shelf optimization algorithms—a global genetic algorithm (GA) and multistart gradient-based sequential quadratic programming (SQP) and quasi-Newton (BFGS) algorithms. For the analytical test...

...A. J. Knoek van Soest; L. J. R. Richard Casius A parallel genetic algorithm for optimization is outlined, and its performance on both mathematical and biomechanical optimization problems is compared to a sequential quadratic programming algorithm, a downhill simplex algorithm and a simulated...

...Jacob L. Jaremko; Philippe Poncet; Janet Ronsky; James Harder; Jean Dansereau; Hubert Labelle; Ronald F. Zernicke Scoliosis severity, measured by the Cobb angle, was estimated by artificial neural network from indices of torso surface asymmetry using a genetic algorithm to select the optimal set...