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- PEGA make up for their lacks and genetic operation of PEGA is much simper than traditional genetic algorithm. 与传统的遗传算法相比,PEGA算法弥补了它们的不足之处,简化了遗传算法。
- IGA avoids effectively the common defects of early convergence and the diversity of population in traditional genetic algorithm. 该算法摆脱了对群体多样性的要求，不存在传统遗传算法常见的“早熟收敛”问题。
- Based on the model, an optimization algorithm called GP-GA was proposed by hybridizing Gene-Pool (GP) with traditional Genetic Algorithm (GA). 在此模型的基础上提出了一种基因库(GP)与传统遗传算法(GA)混合的优化算法GP-GA。
- Traditional genetic algorithm is promoted.As far as the construction of fitness function, it adds the measure of symmetry, uniformity and smoothness. 对原有的遗传算法做了改进，在适应度函数构建方面增加了对称度、均匀度和平滑度的度量。
- The simulation results and comparison with the traditional genetic algorithm show the efficiency of this approach especially to the large scale prob. 进一步,仿真试验结果及与传统遗传算法的比较证明了这一算法对大规模机器布置问题的有效性。
- It performs reconstruction operation on a single chromosome. In PGA, some new operatorssuch as Geng Exchange have erplaced the crossover operator in traditional Genetic Algorithm. 它在同一条染色体上采用基因换位等算子进行染色体重组,取消了传统遗传算法中的交叉算子。
- IGA was applied into PID controller parameters optimization.Compared with traditional genetic algorithm(TGA), the simulation results prove that IGA is more efficient. 将其应用于PID控制器的参数优化中，并与传统的遗传算法相比较，仿真结果证明了其有效性。
- This design is aimed at the shortcoming of the traditional genetic algorithm,such as slow training speed,premature,easy to be trapped into local optimums. 通过使用本方法可以有效地改善了采用传统遗传算法用于处理同类问题时的种群分布不均匀陷入局部最优、未成熟收敛等缺陷。
- To overcome the shortcoming, a genetic algorithm of schema oriented is proposed based on the improvement of the technological process of traditional genetic algorithm. 为了克服此缺陷，在对传统遗传算法流程做出重大改进的基础上，提出了以模式为导向的遗传算法。
- Then in view of the disadvantages of the traditional genetic algorithm for UTP, the diploid code was put forward and alternate evolution was used to optimize multi-targets one by one. 然后针对用传统遗传算法求解UTP所存在的问题，提出双倍体编码方案，并利用交替进化的方法，对多个目标逐个循环优化。
- Based on many features of genetic algorithm applied to optimization design, the improvements on traditional genetic algorithm were made on the basis of diagnosis of deconvolution signal. 利用遗传算法在优化设计中的诸多特性，对传统的遗传算法进行了基于反卷积信号诊断的改进。
- The authors improved the traditional genetic algorithm, and combined the new method named RAGA (Real coding based on Accelerating Genetic Algorithm) with PPE (Projection Pursuit Evaluation) model. 提出将改进的实码加速遗传算法(RAGA)与投影寻踪评价模型(PPE)相结合,同时优化多维参数(投影方向),建立了多元数据分类与评价模型。
- The new algorithm presented in this paper combines traditional genetic algorithms with chaos theory by the full use of the property of ergodicity of chaos movement,expected to improved th... 这种算法将混沌序列嵌入标准遗传算法,对标准遗传算法的个体进行混沌化处理,利用混沌的遍历特性来改进遗传算法的鲁棒性。
- By contrasting the traditional genetic algorithms (TGA) with the biologic evolution, two kinds of reasons that the convergence speed and searching efficiency in TGA are both lower are concluded. 摘要比照传统遗传算法与生物界进化过程，分析了引起传统遗传算法收敛速度慢和寻优效率低的两个原因。
- So what is the genetic algorithm? 那么什么是遗传算法呢?
- A real zooming genetic algorithm is put forth. 进而提出基于实数编码的变焦遗传算法。
- Traditional genetic interactions such as suppressors, synthetic lethals, etc. 传统的遗传交互作用例如抑制物、合成致死,等等。
- A genetic algorithm with a dual fitness function was proposed. 摘要提出一个具有对偶适应度函数的遗传算法。
- Section for the link to the Genetic Algorithms FAQ. 中遗传算法常见问题解答的链接部分。
