applies feed forward neural network to the n queens question, and sdves the local minimization question using a rapid learning algorithm with variable learning factors.
提出三阶变系数发展方程的的局部问题,按文章里的方法来推出问题解的黎曼函数表示的公式,然后用黎曼方法证明解的唯一性。
to avoid the disadvantage of artificial potential field, a method was put forward to separate the region which will result in local minimization by some special points.
针对人工势场法中局部极小问题产生的根源,提出将现场中容易导致局部极小问题的区域通过一些人为设置的特征点隔离出来。
applies feed forward neural network to the n queens question, and sdves the local minimization question using a rapid learning algorithm with variable learning factors. gives several research results.
采用前馈神经网络求解n-皇后问题,并用变学习因子的快速学习算法解决局部极小化问题,给出了几组搜索结果。
through comparing calculation with typical examples, it shows that the question of local minimization can be avoided effectively using the improved algorithm, so the method has practicability.
计算结果与典型算例对比证明:改进后的模拟退火算法能够有效避免局部最优解,方法具有实用性。