1) Shared Global Optimization Algorithm
共享式全局寻优算法
2) global optimization approach
全局寻优搜索算法
4) global optimization
全局寻优
1.
A function optimization problem is presented to demonstrate the feasibility of this method as well as demonstrating the global optimization functionality of genetic algorithm.
探讨了在ＭＡＴＬＡＢ环境中实现遗传算法仿真的方法，并以一个简单的求函数最值的问题作为遗传算法的应用实例，说明遗传算法的全局寻优性及用ＭＡＴＬＡＢ实现仿真的可行性。
2.
In this paper, the authors describe a new global optimization strategy to solve some problems such as the initial model sensitivity, frequent local traps for the conventional impedance inversion based on model in the method searching model based on genetic algorithm is added into the calculating flow of logging constraint inversion.
针对常规基于模型的波阻抗反演方法严重依赖于初始模型的选择和易陷入局部最优等局限性,提出了一种新的全局寻优策略。
3.
This paper presents a new inversion algorithm,quantum genetic algorithm,which adopts the qubit chromosomes as presentations and updates the population using quantum rotation gate,to accelerate the search speed,to improve convergent efficiency,and to get a better global optimization.
量子遗传算法QGA(Quantum Genetic Algorithm)以量子理论为基础,通过量子位编码和量子旋转门更新种群来寻找全局最优,加快了搜索速度,具有更强的全局寻优能力。
5) GCAQBP
全局寻优自适应的快速BP算法
6) Combined global search optimization algorithm
组合式全局优化算法
补充资料：全局最优值
分子式：
CAS号：
性质：又称全局最优值。最优化问题中从整体考虑求得的最优结果。全局最优点可能不只一个，但全局最优值只有一个。
CAS号：
性质：又称全局最优值。最优化问题中从整体考虑求得的最优结果。全局最优点可能不只一个，但全局最优值只有一个。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条