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Proposing a new algorithm which is simple but effective. Using characteristic of biological evolution and common sense to design the selection operator, improve the variation method of the crossover probability and the mutation probability. Numerical experiments show that the new algorithm is more effective than the comparative algorithm in realizing the high convergence speed, convergence precision,...
A new self-adaptive mind evolutionary algorithm based on information entropy is proposed to improve the algorithmic convergence especially in the late evolutionary time. As studied, the evolution of a population is a process with entropy reducing and the population entropy can be used to reflecting the evolution state. Thus the self-adaptive strategy can be realized by building population entropy...
The commercial banks risks come from all the uncertainty of the banking business, which have diffusibility and hidden features, if not timely controlled, will have a negative impact on the national economy. Therefore, it is necessary to design the corresponding index system according to the objectivity and relativity of the banking risks, and then control quantitatively the banks risk. Based on the...
This paper studies various training algorithms of BP neural network and proposes an improved conjugate gradient algorithm which combines conjugate gradient algorithm with inexact line search route based on generalized Curry principle. The proposed algorithm has global convergence, optimizes the learning steps using new line search rules and improves the convergence speed. The new algorithm is applied...
In this paper, we present a novel adaptive step-size and block-size frequency-domain block least mean square (ASB-FBLMS) algorithm. The convergence speed and the steady stage error are two conflicting factors in the traditional frequency-domain block least mean square (FBLMS) algorithm. While our algorithm optimally increase the convergence speed while maintaining or reducing the steady stage error...
A novel dynamic particle swarm optimization algorithm based on chaotic mutation (DCPSO) is proposed to solve the problem of the premature and low precision of the common PSO. Combined with linear decreasing inertia weight, a kind of convergence factor is proposed based on the variance of the populationpsilas fitness in order to adjust ability of the local search and global search; The chaotic mutation...
In this paper, the particle swarm optimizer is modified to create the multi-swarm accelerating PSO which is applied to dynamic continuous functions. Different from the existing multi-swarm PSOs and local versions of PSO, the swarms are dynamic and the swarms' size is small. The whole population is divided into many small swarms, these swarms are regrouped frequently by using various regrouping schedules...
This paper introduces triangulation theory into genetic algorithm and with which, the optimization problem will be translated into a fixed point problem. An improved genetic algorithm is proposed by virtue of the concept of relative coordinates genetic coding, designs corresponding crossover and mutation operator. Through genetic algorithms to overcome the triangulation of the shortcomings of human...
This paper introduces triangulation theory into genetic algorithm and with which, the optimization problem will be translated into a fixed point problem. An improved genetic algorithm is proposed by virtue of the concept of relative coordinates genetic coding, designs corresponding crossover and mutation operator. Through genetic algorithms to overcome the triangulation of the shortcomings of human...
Using 3D information delivered by laser range sensor becomes more and more common in industrial systems. Especially object recognition and localization in 3D range data is still a challenging task in robotic vision. We connect the registration technique of the well known iterative closest points algorithm with the hierarchical object representation of progressive meshes to find objects in a scene...
The continuous physical-mathematical model of the 3D structures of protein has been obtained by analyzed the 3D structures of biological protein according to the distance and dihedral angle distribution of amino acid residue conforming to Boltzmann theorem. On this foundation, stretches of the B (D) main chain for the bovine insulin have been calculated by application of the improved simulated annealing...
In a multi-hop mobile ad hoc network (MANET), mobile nodes communicate with each other forming a cooperative radio network. Security remains a major challenge for these networks due to their features of open medium, dynamically changing topologies, reliance on cooperative algorithms, absence of centralized monitoring points, and lack of any clear lines of defense. Most of the currently existing intrusion...
Based on a parametric planar rotation updated algorithm and the deflation technique, a blind signal extraction method is proposed in underdetermined mixtures. While extracting one, source signal from the mixtures and keeping size of the mixtures, a separated signal is concealed from the mixtures using the deflation technique. This procedure is repeated for the deflated mixtures until all source signals...
Based on neural network, an improvement scheme that iterative matrix replace secondary derivative has been developed by introduced quasi-Newton algorithm. Profile code based on probability has been used and comparison of window width and learning training has been completed. The experiment results indicate that the prediction for secondary structures of protein obtain a very good effect based on neural...
In order to improve some fundamental problems of the clonal selection algorithm (CSA), a novel clonal selection algorithm (NCSA) is proposed. After analyzing the mechanism of the clonal selection and proposing the antibody model, the basic character of the application problem fused into the NCSA based on rearrangements of antibody molecule coding genes. Next, we analyzed synthetically the antibody-antigen...
A space mapping algorithm with improved convergence properties for microwave design optimization is presented. In contrast to the previously published technique, a new convergence control method can be applied to surrogate models using non-extractable parameters, in particular, the output space mapping one of the most useful approaches to date. We demonstrate that the new algorithm allows for faster...
In this paper we present a centralized flow control scheme in NoCs in the presence of both elastic and streaming flow traffic paradigms. We model the desired best effort (BE) source rates as the solution to an alpha-fair utility maximization problem which is constrained with link capacities while preserving guaranteed service (GS) traffic requirements at the desired level. We propose an iterative...
The complexity and dynamics of Border Gateway Protocol (BGP), the only inter-domain routing protocol available for the Internet, is driving the need for efficient, scalable, realistic and meaningful network simulations. To properly simulate the behavior of BGP as currently deployed, one requires both a realistic topology and a realistic model of BGP. Although a large number of topology generators...
An adaptive sinusoidal interference cancellation system is analyzed in time-domain. Through the evaluation of the time-varying difference equation group, exact analytical solutions are gained. The necessary and sufficient condition for the convergence of the system and the step size mu which makes the system converge fastest are calculated. For LMS (least mean squares) algorithm, the two-step convergence...
In terms of Gauss-Newton (G-N) nonlinear least-squares algorithm, if J(x) is rank-deficient, then either the Gauss-Newton method cannot work well, or the algorithm converges to a non-stationary point. To overcome the difficulty, in this paper we consider employing trust-region technique, and propose Levenberg-Marquardt (L-M) algorithm. In L-M algorithm, damping term mukI is added to G-N algorithm...
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