An improved evolutionary programming algorithm is proposed for fuzzy programming problems. The idea is to mimic the physics of electromagnetism by considering each individual as an electrical charge. Charge of each in...
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An improved evolutionary programming algorithm is proposed for fuzzy programming problems. The idea is to mimic the physics of electromagnetism by considering each individual as an electrical charge. Charge of each individual is defined using membership functions. After calculating these charges, like the electromagnetic force, we calculate a combination force exerted on each individual. This combination force is regarded as the search direction of mutation operator. The fitness function is given by membership functions. A fuzzy model is developed for designing 3D trajectory of horizontal wells. The fuzzy model can be transformed to fuzzy programming problem and solved by our proposed method. The model is illustrated numerically and the results are efficiently.
It is difficult for basic genetic algorithm and evolutionary programming algorithm to converge at global optimal solution of real-continual function in practice, although both of the algorithms have the ability for ge...
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It is difficult for basic genetic algorithm and evolutionary programming algorithm to converge at global optimal solution of real-continual function in practice, although both of the algorithms have the ability for getting the global optimal solution with convergent probabilities 1 in theory. In this paper, a new hybrid genetic algorithm based on clan competition is proposed, and it is proved that the probability of the new algorithm convegent to the global optimal solution is 1, Numerical experiments results illustrate that, compared with the former two algorithms, the new algorithm is the robustest among the three algorithms, what's more, it has the highest precision with the equal parameters.
This paper is concerned with the synchronization problem of optical chaos in vertical-cavity surface-emitting lasers (VCSELs). A proportional-integral (PI) controller is proposed to achieve the synchronization. An evo...
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This paper is concerned with the synchronization problem of optical chaos in vertical-cavity surface-emitting lasers (VCSELs). A proportional-integral (PI) controller is proposed to achieve the synchronization. An evolutionaryprogramming (EP) algorithm is newly introduced for deriving optimal or near optimal PI control gains, such that a specified performance index between the master and slave VCSELs is minimized. A numerical result exemplifies the synchronization procedure. (c) 2008 Elsevier Ltd. All rights reserved.
This paper is concerned with the optimum setting problem for deriving gains in proportional-integral-derivative (PID) controllers. The evolutionaryprogramming (EP) algorithm has been considered as a useful technique ...
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This paper is concerned with the optimum setting problem for deriving gains in proportional-integral-derivative (PID) controllers. The evolutionaryprogramming (EP) algorithm has been considered as a useful technique for finding global optimization solutions for certain complicated functions ill recent years. Therefore, in this paper, we attempt to use the EP algorithm in PID control systems design for deriving optimal or near optimal PID control gains such that a performance index of integrated-absolute error (IAE) is minimized. It can be easily seen from the simulation results that the proposed method will have better performance than those presented in other studies by testing a fourth-order system with time delay.
Based on the clonal selection theory, the main mechanism of immune clone applied in artificial intelligence is analyzed in this paper. A new operator, Adaptive Polyclonal Operator as well as a novel artificial immune ...
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ISBN:
(纸本)0769519571
Based on the clonal selection theory, the main mechanism of immune clone applied in artificial intelligence is analyzed in this paper. A new operator, Adaptive Polyclonal Operator as well as a novel artificial immune system algorithm, APPA (Adaptive Polyclonal programmingalgorithm), is put forward. Compared with some other evolutionary programming algorithms (like Breeder Genetic algorithm), APPA, behaving as an evolutionary strategy, is shown to be capable of solving complex machine learning tasks effectively, like Multimodal function Optimization.
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