Genetic algorithm is used widely for the optimization, and some problems bother with users long time, such as prematurity, how to select proper operators, etc. Illuminated from the atavism in organic evolution, backtr...
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ISBN:
(纸本)9783642549243;9783642549236
Genetic algorithm is used widely for the optimization, and some problems bother with users long time, such as prematurity, how to select proper operators, etc. Illuminated from the atavism in organic evolution, backtracking is banded together with genetic algorithm to solve the problem of prematurity. This method makes genetic algorithm out of local optimum, and prematurely, converging problem is solved with the selection of proper backtracking strategy, which includes partial backtracking, and variable distance sampling, etc. Then, the traveling seller problem is solved with an elaborate design of genetic operators, and pruning method is used to insure higher convergence velocity. The simulation experiment indicates that this algorithm can get preferable result than others.
In this paper by utilizing evolution algorithm we proposed an optimization method for manifold block design by using visual basic 6.0 programs. In our designed visual basic 6.0 programs the geometric parameters of hyd...
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ISBN:
(纸本)9781424427239
In this paper by utilizing evolution algorithm we proposed an optimization method for manifold block design by using visual basic 6.0 programs. In our designed visual basic 6.0 programs the geometric parameters of hydraulic elements are putted into special designed drawing interface procedure, so the manifold block drawing of hydraulic system can be automatically produced by our designed procedure. At finally, the numerical results by the designed procedure implies that the computational efficiency is greatly improved and the computational time of designing is largely shortened.
Applying evolution algorithm to selection of security elliptic curve(EC) is first researched in the paper. In order to ensure the security of elliptic curve cryptosystem(ECC), it is necessary that the elliptic curves ...
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ISBN:
(纸本)9780769536453
Applying evolution algorithm to selection of security elliptic curve(EC) is first researched in the paper. In order to ensure the security of elliptic curve cryptosystem(ECC), it is necessary that the elliptic curves are safe against all kinds of attack algorithms about the elliptic curve discrete logarithm problem (ECDLP). Therefore, selection of secure elliptic curves is a mathematics difficult problem. In this paper, selection principles of secure EC are firstly analyzed. Then, based on the selection principle, a selection algorithm of security EC based on evolution algorithm is put forward. The thoughts of encoding, crossover and mutation of evolution algorithm for selection of EC are discussed in detail. The implementation result shows the availability and efficiency of the algorithm.
In this paper, an estimation of distribution algorithm(EDA) is proposed. SWFZIRS(Sector Window Floating Zoom Immune Random Search) operator has been utilized in fitness calculation. The Gaussian distribution has been ...
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In this paper, an estimation of distribution algorithm(EDA) is proposed. SWFZIRS(Sector Window Floating Zoom Immune Random Search) operator has been utilized in fitness calculation. The Gaussian distribution has been utilized in the estimation of distribution. Experiments show that the algorithm can improve increasing the probability of obtaining the global optimal solution. It can almost obtain the global optimal solution in two-dimension space.
The emerging large-scale biological tools (e. g., microarray) challenge biologists to realize the connectivity of genes and/or proteins at the system level (global view). Having advantages in good generalization and s...
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ISBN:
(纸本)9780769550053
The emerging large-scale biological tools (e. g., microarray) challenge biologists to realize the connectivity of genes and/or proteins at the system level (global view). Having advantages in good generalization and showing the direct interaction of genes and/or proteins, the S-system becomes one of the popular models, which is able to capture the dynamic behavior of the biological system. Differential evolution (DE) and its variants have recently applied to solve various optimization problems in engineering fields. However, the exploitative and explorative abilities are insufficient. In this study, we propose a winner-take-all memetic differential evolution scheme to infer the parameters of the S-type gene regulatory networks. This method was tested with a genetic-branch pathway and a twenty-gene network. The learning was implemented in a wide search space ([0, 100] for rate constants and [-100, 100] for kinetic orders) with a bad initial start (All parameters were randomly initialized at the neighborhood of 80). Simulation results show high-accuracy solutions are obtained.
A three-phase memetic algorithm (MA) is proposed to find a suboptimal solution for real-time combinatorial stochastic simulation optimization (CSSO) problems with large discrete solution space. In phase 1, a genetic a...
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A three-phase memetic algorithm (MA) is proposed to find a suboptimal solution for real-time combinatorial stochastic simulation optimization (CSSO) problems with large discrete solution space. In phase 1, a genetic algorithm assisted by an offline global surrogate model is applied to find N good diversified solutions. In phase 2, a probabilistic local search method integrated with an online surrogate model is used to search for the approximate corresponding local optimum of each of the N solutions resulted from phase 1. In phase 3, the optimal computing budget allocation technique is employed to simulate and identify the best solution among the N local optima from phase 2. The proposed MA is applied to an assemble-to-order problem, which is a real-world CSSO problem. Extensive simulations were performed to demonstrate its superior performance, and results showed that the obtained solution is within 1% of the true optimum with a probability of 99%. We also provide a rigorous analysis to evaluate the performance of the proposed MA.
Gene Expression programming (GEP) is a new algorithm of evolutionary computation, which possesses much more powerful abilities of parallel computation and global search to resolve complex problems. This paper construc...
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ISBN:
(纸本)9781467347143
Gene Expression programming (GEP) is a new algorithm of evolutionary computation, which possesses much more powerful abilities of parallel computation and global search to resolve complex problems. This paper constructs the GEP classification model and carries out experiments with Landsat Thematic Mapper(TM) image of Dongguan city in 1997. The result shows that the GEP classification model has good classification accuracy and demonstrates effectiveness in remote sensing image classification.
In this paper by utilizing evolution algorithm we proposed an optimization method for manifold block design by using visual basic 6.0 *** our designed visual basic 6.0 programs the geometric parameters of hydraulic el...
详细信息
In this paper by utilizing evolution algorithm we proposed an optimization method for manifold block design by using visual basic 6.0 *** our designed visual basic 6.0 programs the geometric parameters of hydraulic elements are putted into special designed drawing interface procedure,so the manifold block drawing of hydraulic system can be automatically produced by our designed *** finally,the numerical results by the designed procedure implies that the computational efficiency is greatly improved and the computational time of designing is largely shortened.
In this paper by utilizing evolution algorithm we proposed an optimization method for manifold block design by using visual basic 6.0 programs. In our designed visual basic 6.0 programs the geometric parameters of hyd...
详细信息
In this paper by utilizing evolution algorithm we proposed an optimization method for manifold block design by using visual basic 6.0 programs. In our designed visual basic 6.0 programs the geometric parameters of hydraulic elements are putted into special designed drawing interface procedure, so the manifold block drawing of hydraulic system can be automatically produced by our designed procedure. At finally, the numerical results by the designed procedure implies that the computational efficiency is greatly improved and the computational time of designing is largely shortened.
Walking is the basic skill of a legged robot, and one of the promising ways to improve the walking performance and its adaptation to environment changes is to let the robot learn its walking by itself. Currently, most...
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Walking is the basic skill of a legged robot, and one of the promising ways to improve the walking performance and its adaptation to environment changes is to let the robot learn its walking by itself. Currently, most of the walking learning methods are based on robot vision system or some external sensing equipment to estimate the walking performance of certain walking parameters, and therefore are usually only applicable under laboratory condition, where environment can be pre-defined. Inspired by the rhythmic swing movement during walking of legged animals and the behavior of their adjusting their walking gait on different walking surfaces, a concept of walking rhythmic pattern（WRP） is proposed to evaluate the walking specialty of legged robot, which is just based on the walking dynamics of the robot. Based on the onboard acceleration sensor data, a method to calculate WRP using power spectrum in frequency domain and diverse smooth filters is also presented. Since the evaluation of WRP is only based on the walking dynamics data of the robot＇s body, the proposed method doesn＇t require prior knowledge of environment and thus can be applied in unknown environment. A gait learning approach of legged robots based on WRP and evolution algorithm（EA） is introduced. By using the proposed approach, a quadruped robot can learn its locomotion by its onboard sensing in an unknown environment, where the robot has no prior knowledge about this place. The experimental result proves proportional relationship exits between WRP match score and walking performance of legged robot, which can be used to evaluate the walking performance in walking optimization under unknown environment.
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