This work is to provide general spectral and pseudo-spectral Jacobi-Petrov-Galerkin approaches for the second kind Volterra integro-differential *** Gauss-Legendre quadrature formula is used to approximate the integra...
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This work is to provide general spectral and pseudo-spectral Jacobi-Petrov-Galerkin approaches for the second kind Volterra integro-differential *** Gauss-Legendre quadrature formula is used to approximate the integral operator and the inner product based on the Jacobi weight is implemented in the weak formulation in the numerical *** some spectral and pseudo-spectral Jacobi-Petrov-Galerkin methods,a rigorous error analysis in both L2_(ω^(α,β))^(2),and L^(∞)norms is given provided that both the kernel function and the source function are sufficiently *** experiments validate the theoretical prediction.
The gene section ordering on solving traveling salesman problems is analyzed by numerical experiments. Some improved crossover operations are presented. Several combinations of genetic operations are examined and the ...
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The gene section ordering on solving traveling salesman problems is analyzed by numerical experiments. Some improved crossover operations are presented. Several combinations of genetic operations are examined and the functions of these operations are analyzed. The essentiality of the ordering of the gene section and the significance of the evolutionary inversion operation are discussed. Some results and conclusions are obtained and given, which provide useful information for the implementation of the genetic operations for solving the traveling salesman problem.
Computational intelligence is the computational simulation of the bio-intelligence, which includes artificial neural networks, fuzzy systems and evolutionary computations. This article summarizes the state of the art ...
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Computational intelligence is the computational simulation of the bio-intelligence, which includes artificial neural networks, fuzzy systems and evolutionary computations. This article summarizes the state of the art in the field of simulated modeling of vibration systems using methods of computational intelligence, based on some relevant subjects and the authors' own research work. First, contributions to the applications of computational intelligence to the identification of nonlinear characteristics of packaging are reviewed. Subsequently, applications of the newly developed training algorithms for feedforward neural networks to the identification of restoring forces in multi-degree-of-freedom nonlinear systems are discussed. Finally, the neural-network-based method of model reduction for the dynamic simulation of microelectromechanical systems (MEMS) using generalized Hebbian algorithm (GHA) and robust GHA is outlined. The prospects of the simulated modeling of vibration systems using techniques of computational intelligence are also indicated.
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