SGAS

Simple genetic algorithms ( SGAs ) is utilized to study the simulation technique of the system reliability optimization of a serial-parallel redundancy model .

利用简单遗传算法（simplegeneticalgorithms，SGAs）研究了系统的可靠性优化仿真技术；

Furthermore , a low bound is estimated to the probability of SGAs , converging to the premature set .

同时，我们对于算法收敛于早熟集的概率给出了一个下界估计。

In order to improve SGAs optimization ability and to prolong its searching process , a new genetic algorithm based on a completely self-adaptive strategy is put forward .

为改善标准遗传算法的优化性能，延长种群搜索过程，提出了完全自适应策略的遗传算法。

Background : Antipsychotic drugs are the first choice for treatment psychosis , mainly divided into two categories , the first generation of atypical drugs ( FGAs ) and second-generation atypical drugs ( SGAs ) .

背景：抗精神药物为精神病的首选药物，主要分为两大类，第一代典型性抗精神药物和第二代非典型性抗精神药物。

To find Simvastatin and Berberine combined with Olanzapine through this model , can interfere with lipid metabolism side effects of olanzapine which is the representative of SGAs , provide the basis for clinical drug combination .

通过应用此模型，筛选到Simvastatin和Berberine与Olanzapine联合用药，能在一定程度上干预SGAs的代表药物olanzapine引起的脂代谢副作用，为临床上联合用药提供理论基础。

Applying the homogeneous finite markov chain , the means of the simple genetic algorithm limit analysis is given , the conclusions that the simple genetic algorithm ( SGAS ) is not global convergent and the maintaining optimum SGAS ( MOSGAS ) is global convergent are drawn .

应用齐次有限马尔科夫链为工具，给出了基本遗传算法（SGAS）的收敛性分析方法，并得出了基本遗传算法不是全局收敛，最优保存简单遗传算法（MOSGAS）是全局收敛的结论。