| 1. | Finally , using the obtained results , the local optimal solution of a given example is obtained
最后借助得到的结果求得了一个算例的局部最优解。 |
| 2. | 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。 |
| 3. | Mean shift algorithm is an applied algorithm that calculates local optimal result fast and effectively
而均值平移( meanshift )算法是计算局部最优解的一个实用的算法，具有快速和有效的特点。 |
| 4. | 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。 |
| 5. | Aiming at multiple frames video sequences with moving objects , a new image mosaic method imitating compound eyes is presented based on image ' s characteristic . now . some mosaic algorithms are local optimizing
两种方法克服了现存的图像拼合算法只能得到局部最优解的缺点，对图像样本的要求大大降低，而且可以得到全优解。 |
| 6. | In order to improve the population performance , the individual local searching is used to get the local optimization on the environment . finally , the comparison of algorithm efficiency is given
基于群体中各个个体所对应的表现型，进行局部搜索，从而找出各个个体在目前环境下的局部最优解，以便达到改善群体总体性能的目的。 |
| 7. | But in fact , in the design of the deep excavations , which deals with many factors , the variables are discrete and the aim function has more than one peak value . so the traditional optimal methods often run into the local optimal value
实际上，在深基坑工程设计中，涉及因素很多，变量是离散的，目标函数也是多峰的，利用传统的优化方法，往往使算法陷入局部最优解。 |
| 8. | The algorithm can effectively o vercome immature convergence phenomenon in simple genetic algorithm ( sga ) . it can improve not only antibody ' s similarity but also its diversity . and it can avoid local optimal solution and shorten searching time
该算法可以有效地克服基本遗传算法的未成熟收敛现象，既可以提高抗体的相似性又可以兼顾到抗体的多样性，为避免算法陷入局部最优解，缩短搜索时间提供了保证。 |
| 9. | The bfgs algorithm applied in gcs is analyzed and pointed out two shortcomings : ( 1 ) always trapped in local optimal solution ; ( 2 ) can not pass through the critical point . these shortcomings make the bfgs algorithm can not find the global best solution
分析了bfgs算法在约束求解中的应用，指出了在约束求解这一特定的领域利用bfgs算法进行约束求解的两大缺陷： ( 1 )容易陷入局部最优解： ( 2 )无法穿越临界点。 |
| 10. | The algorithm can implement the diversity of solution , avoid converging local optimal solution , and prevent the possibility of losing optimal solution effectively , by holding some optimal chromosomes in each generation and introducing expectation reproduction rate
通过保留每代最佳的若干染色体以及引入期望繁殖率的概念，本算法可以实现解的多样性，避免收敛于局部最优解，同时可以有效的防止在进化的过程中失去最优解的可能性。 |
