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An improved adaptive genetic algorithm for solving facility layout problem is proposed. The principle of the algorithm is: during running process, making the crossover and mutation possibility adjust adaptively along with the value of fitness in accordance with the laws of sigmoid function curve; using smaller crossover and mutation possibility for the individuals of better patterns while lager crossover...
Based on the optimization problem of the number and size in coal mine equipment the principle and procedure of genetic algorithm is introduced. The case of application proves that the genetic algorithm can better optimize the number and size of equipments in coal mine.
The constraint conditions of the auto-generating test paper are analyzed. The mathematical model of intelligence test paper generation system is set up and a new method of composing test paper based on the improved genetic algorithm is given. The result of the experiments shows that the new method is more efficient and easier to deal with the problem of autogenerating test paper than the traditional...
Simple genetic algorithm is prone to premature and has a slow convergence. In view of the above inadequacies, we carried on an optimal design of selection operation and proposed a model of selection operation creatively in this paper. That is the strategy of ultra expectations - compared selection. Besides, we proved its advantages in global optimal solution and convergence speed. It can avoid effectively...
Neural network and genetic algorithm have attracted a great deal of attention as methods and theories realizing artificial intelligence recently. The combination of these two is drawing more and more attention. This paper demonstrates the possibility of combining neural network with genetic algorithm. An improved genetic algorithm for the learning of neural network's connection weights is presented...
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