| 1. | That they are easy to fall into a local optimum is the shortcoming of conventional optimization methods
传统的优化方法，即所谓的确定性优化方法的突出缺陷是容易陷入局部最优解。 |
| 2. | The registration results showed that the subvoxel accuracy could be achieved and this method can avoid getting into the local optimum
实验表明，该算法能避免陷入局部最优值，配准结果精度达到亚像素级。 |
| 3. | Optimization of complex systems is often characterized by large scale , complex constraints , high nonlinearity and multiple local optima
优化技术是一门重要的科学分支，在许多工程领域得到推广和应用。 |
| 4. | Experimental results verify the theoretical performance analysis and show that the performance of the local optimum detector is better than that of the linear correlate detector
实验验证了图像水印检测理论的有效性以及本文的局部优化检测器性能的优良性。 |
| 5. | The basic principle of cpso algorithm is that chaos initialization is adopted to improve individual quality and chaos perturbation is utilized to avoid the search being trapped in local optimum
该算法的思想是采用混沌初始化进行改善个体质量和利用混沌扰动避免搜索过程陷入局部极值。 |
| 6. | In the hybrid approach , based on the global search ability , discrete artificial immune algorithm is used to search the optimal solution and simulated annealing is applied to avoid getting into a local optimum
该方法利用离散人工免疫算法的全局搜索能力来寻找全局最优解，利用模拟退火方法来避免陷入局部最优。 |
| 7. | The algorithms is carried into training connection weights of nn and simulation experiments show the arithmetic can escape local optima and improve learning speed of nn to some extent
将其用于调整神经网络的连接权值，实验证明该方法可克服神经网络训练的局部最优解问题，并在一定程度上提高神经网络的学习速度。 |
| 8. | Aim at the neural network get local optimum easily , the speed of convergence is slow , the quantity of training excessive and so on . this paper adopted the ga optimize the nn firstly , and then the nn algorithm
针对神经网络易出现局部最优点、收敛速度慢和训练量过大等问题,本文先利用遗传算法对神经网络进行优化后,再执行神经网络的算法步骤。 |
| 9. | A high precision chaotic optimization strategy was applied to parameter identification of power system static load model and the deficiency of traditional methods were effectively overcome which are easily being trapped in local optima
将一种高精度的混沌优化策略用于电力系统静态负荷模型参数辨识，克服了传统的基于梯度寻优的辨识方法容易陷入局部最优点的不足。 |
