Genetic algorithm(GA) has a good robust and global optimization *** this paper,a supercavitation regime problem is transformed into an equivalent shape optimization problem by defining the objective function as a squa...
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Genetic algorithm(GA) has a good robust and global optimization *** this paper,a supercavitation regime problem is transformed into an equivalent shape optimization problem by defining the objective function as a square error integral of pressure *** combining the commercial CFD soft ANSYS with GA,this problem has been solved *** show that genetic algorithm is feasible and effective used in supercavitation flow analysis,the method is good for the reduction of computational complexity and more *** the frame can be expanded to study the cavitator optimization in which the regime optimization can be as a sub-optimization.
In this paper, a new method is presented for double nonlinear analysis of the simply-supported beam with elastic-perfectly plastic model. The major character of the new method is that the equilibrium state with elasti...
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In this paper, a new method is presented for double nonlinear analysis of the simply-supported beam with elastic-perfectly plastic model. The major character of the new method is that the equilibrium state with elastic-plastic large deformation is chosen as the study object. The constitutive law adopts elastic-perfectly plastic model and the shearing deformation is taken into account. The endpoint coordinates are given by means of coordinate recursion formulae, and the objective function is defined by unknown endpoint coordinates of slight segments. The optimization problem is established for double nonlinear analysis of the simply-supported beam, and the optimization program is programmed. Typical numerical examples are calculated by optimization algorithm, and the results are in very good agreement with those by FEM. So this paper provides a new and effective idea for double nonlinear problem of the simply-supported beam.
A Mobile Ad hoc NETwork (MANET) is an autonomous system of mobile nodes connected by wireless links There is no static infrastructure such as base station as that was in cell mobile communication. Due to the dynamic n...
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ISBN:
(纸本)0769524052
A Mobile Ad hoc NETwork (MANET) is an autonomous system of mobile nodes connected by wireless links There is no static infrastructure such as base station as that was in cell mobile communication. Due to the dynamic nature of the network topology and restricted resources, quality of service (QoS) and multicast routing in MANET is a challenging task In this paper, we present an entropy-based model to support QoS multicast routing optimization algorithm in mobile ad hoc networks (EQMOA). The basic motivations or the proposed modeling approach stem from the commonality observed in the location uncertainty in mobile ad hoc wireless networks and the concept of entropy. The simulation results demonstrate that the proposed approach and parameters provide an accurate and efficient method of estimating and evaluating the route stability in dynamic mobile networks.
A Mobile Ad hoc NETwork (MANET) is an autonomous system of mobile nodes connected by wireless links. There is no static infrastructure such as base station as that was in cell mobile communication. Due to the dynamic ...
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ISBN:
(纸本)078039335X
A Mobile Ad hoc NETwork (MANET) is an autonomous system of mobile nodes connected by wireless links. There is no static infrastructure such as base station as that was in cell mobile communication. Due to the dynamic nature of the network topology and restricted resources, quality of service (QoS) and multicast routing in MANET is a challenging task. In this paper, we present an entropy-based model to support QoS multicast routing optimization algorithm in mobile ad hoc networks (EQMOA). The basic motivations of the proposed modeling approach stem from the commonality observed in the location uncertainty in mobile ad hoc wireless networks and the concept of entropy. The simulation results demonstrate that the proposed approach and parameters provide an accurate and efficient method of estimating and evaluating the route stability in dynamic mobile networks.
A new approach for the optimization of essentially three-dimensional aerodynamic shapes for minimum drag is proposed. The method allows the handling of the nonlinear surfaces that are typical of complex aircraft junct...
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A new approach for the optimization of essentially three-dimensional aerodynamic shapes for minimum drag is proposed. The method allows the handling of the nonlinear surfaces that are typical of complex aircraft junctions such as a wing-body fairing. The optimization framework OPTIMAS, previously proposed and developed by the authors for the solution of the drag-minimization problem for two-dimensional airfoils, three-dimensional isolated wings, and three-dimensional wings in the presence of a body in succession, is extended in this paper to a significantly higher level of geometrical complexity of optimized aerodynamic configurations. The method is driven by accurate full Navier-Stokes evaluations of the objective function, and the optimization engine is based on genetic algorithms. The important features of the method are the ability to accurately handle multiple geometrical/aerodynamic constraints and a high level of computational efficiency, achieved through massive multilevel parallelization and a reduced-order-model approach. The method was applied to the optimization of a wing-body fairing for a generic business jet configuration at realistic transonic cruise flight conditions. The results demonstrate that the proposed approach achieves significant drag reduction in on- and offdesign conditions and can be used in an engineering environment.
In this paper, we propose a novel optimization algorithm called constrained line search (CLS) for discriminative training (DT) of Gaussian mixture continuous density hidden Markov model (CDHMM) in speech recognition. ...
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In this paper, we propose a novel optimization algorithm called constrained line search (CLS) for discriminative training (DT) of Gaussian mixture continuous density hidden Markov model (CDHMM) in speech recognition. The CLS method is formulated under a general framework for optimizing any discriminative objective functions including maximum mutual information (MMI), minimum classification error (MCE), minimum phone error (MPE)/minimum word error (MWE), etc. In this method, discriminative training of HMM is first cast as a constrained optimization problem, where Kullback-Leibler divergence (KLD) between models is explicitly imposed as a constraint during optimization. Based upon the idea of line search, we show that a simple formula of HMM parameters can be found by constraining the KLD between HMM of two successive iterations in an quadratic form. The proposed CLS method can be applied to optimize all model parameters in Gaussian mixture CDHMMs, including means, covariances, and mixture weights. We have investigated the proposed CLS approach on several benchmark speech recognition databases, including TIDIGITS, Resource Management (RM), and Switchboard. Experimental results show that the new CLS optimization method consistently outperforms the conventional EBW method in both recognition performance and convergence behavior.
One of major problems in image auto-annotation is the difference between the expected word counts vector and the resulted word counts vector. This paper presents a new approach to automatic image annotation-an algorit...
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One of major problems in image auto-annotation is the difference between the expected word counts vector and the resulted word counts vector. This paper presents a new approach to automatic image annotation-an algorithm called resulted word counts optimizer which is an extension to existing methods. An ideal annotator is defined in terms of recall quality measure. On the basis of the ideal annotator an optimization criterion is defined. it allows to reduce the difference between resulted and expected word counts vectors. The proposed algorithm can be used with various image auto-annotation algorithms because its generic nature. Additionally, it does not increase the computational complexity of the original annotation method processing phase. It changes output word probabilities according to a pre-calculated vector of correction coefficients. (C) 2008 Elsevier Ltd. All rights reserved.
Cross-entropy method is base on probability density function. It is robust, easy to use. With analysis of advantages and disadvantages of the cross-entropy method, a directed quantile method based on crossentropy is...
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ISBN:
(纸本)9781424438631;9781424438624
Cross-entropy method is base on probability density function. It is robust, easy to use. With analysis of advantages and disadvantages of the cross-entropy method, a directed quantile method based on crossentropy is proposed. The main idea of the directed quantile cross-entropy method is to select alterable quantity vectors using for producing a "better" sample in the next iteration. The convergence speed and search best result of the directed quantile cross-entropy are tested using 0/1 knapsack problems. The experiments show that the search efficiency of the modified cross-entropy method is more significantly improved than quantum-inspired evolutionary algorithm and cross-entropy method.
The Dual Population Ant Colony optimization(DPACO) was tried to be applied to Power System Dynamic Reactive Power optimization. The installation positions of capacitors were taken as obstacles, the capacities of capac...
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ISBN:
(纸本)9787900719706
The Dual Population Ant Colony optimization(DPACO) was tried to be applied to Power System Dynamic Reactive Power optimization. The installation positions of capacitors were taken as obstacles, the capacities of capacitors installed were taken-as the paths through which the ants climb over the obstacles and the mathematical models of the reactive power planning under the multiple load state were adopted. In running process, the pheromone was adjusted according to the ant's search results and the principle of pheromone modification and the convergence speed was fastened. At the same time, the Dual Population Ant Colony optimization (DPACO) avoided trapping in local optimum and increased the precision of Reactive Power optimization for doing well in global optimization. After optimization, the voltage quality was enhanced obviously and comprehensive fees decrease significantly. The running results show that Dual Population Ant Colony optimization (DPACO) applied to Power System Dynamic Reactive Power optimization is feasible and effective.
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