But BP arithmetic has a low identifying speed and easy to encounter local optimization.
但是BP算法识别速度慢,而且容易陷入局部最优。
The object of the optimization about some practice problem is that search for all local optimization value.
某些实际问题的优化目标是求所有的局部最优解,即求解多峰寻优问题,为了求解多峰优化问题,提出了改造的微粒群优化算法。
Particle swarm optimization algorithm is a swarm intelligence algorithm,which is easily trapped in local optima.
为克服粒子群优化算法容易陷入局部最优的缺点,根据混沌运动的随机性、遍历性特点,提出一种基于混沌思想的粒子群优化算法(CPSO)。
Implied by its three-term structure,the inherent shortcoming that trends to local optima is indicated.
指出其三段式结构所隐含的易陷入局部最优问题,进而提出了一种带有扰动项的改进粒子群算法(PSO-DT)。
The algorithm can generate an optimal local path for obstacle avoidance more efficiently in real time in the dynamic environments, prevent local optimum, and overcome the problem that there is no passage between closely spaced obstacles caused by directly applying the conventional artificial potential field method.
提出了一种基于混沌优化算法的机器人路径规划方法,即混沌人工势场法,该方法能够在动态环境下实时、有效地产生避碰局部最优路径,避免了传统人工势场法容易陷入局部最优和在比较靠近的两个障碍物之间找不到通道的缺陷。
It overcomes the shortcomings of local optimum in some local path planner, like artificial potential field method.
这种方法在局部规划的同时 ,兼备了路径规划的全局性 ,有效地从根本上避免了人工势场法等方法容易陷入局部最优的不足 。
To solve the problem of the number of coalition structure increasing rapidly, OCS algorithm—formation of agent coalition structure based on local optimum is given.
针对多Agent联盟数量是Agent个数指数倍的问题,给出了基于局部最优Agent联盟结构生成算法——OCS算法。
It needs to work out parameters of the base function in the process of finding bias field,but conventional methods such as gradient-descent method often find local best.
在求偏移场的过程中,需要求解基函数的参数,由于传统的梯度下降法易陷入局部最优,为解决此问题,提出将遗传算法引入到参数求解过程中,然而传统的遗传算法不仅时间复杂度高,且易陷入局部最优,为此需对遗传算法进行改进,使得不仅更容易得到全局最优解,且时间复杂度较低。
The authors estimate the bias field by Legendre polynomials to find the parameters with minimum entropy,conventional ways such as gradient-descent method often find local best,to find global best,the authors present genetics algorithm to find best parameters to estimate the bias field,but it can not always find global best neither.
求偏移场的过程中需要求解基函数的参数,由于传统的梯度下降法易陷入局部最优,将遗传算法引入到参数求解过程中,然而传统的遗传算法时间复杂度高,易陷入局部最优,对遗传算法进行了改进,更容易得到全局最优解且时间复杂度较低。
New particle swarm optimization algorithm with global-local best minimum
新的全局—局部最优最小值粒子群优化算法
Research of Reducing Local Optimal Error of Fast Search Algorithms;
降低快速搜索算法中局部最优误差的研究
It can be seen that the object function of the simple model is both non-convex, non-continuous, and has many local optima.
模型曲线形状表明:该优化问题为非凸不连续,具有多个局部最优解;
The results of numerical simulation show that the algorithm has advantages, such as avoiding local optima, high precision solution and simple operations.
数值仿真结果表明该算法具不易陷入局部最优、解的精度高和操作简单等优点。
In this paper NGA was used as the optimization procedure in the constrained background bilinearization (CBBL) of two-way bilinear data in order to reduce the possibility of sinking into local optima.
本文将其引入约束背景双线性化问题的优化求解过程,以避免陷入局部最优.
Markov Random Field Model-Based Image Segmentation Using Local and Global Methods;
基于MRF的局部和全局最优化图象分割方法研究
GENETIC ALGORITHM FOR OPTIMIZING MULTI-APICES FUNCTIONS
求多峰函数全部全局最优解的改进遗传算法
Estimates of the Bounds of Spectral Radius and the Smallest Singular Value of LDD-matrix
局部双严格对角占优矩阵的谱半径上下界与最小奇异值估计
Research on Clustering Protocol Based on Local Minimal Energy Consumption in WSN
无线传感器网络中基于局部能量消耗最优的分簇协议研究
locally asymptotically most powerful test
局部渐近最大功效检验
Provides seven optimization algorithms, three of which are global.
提供七种最优化算法,三种是全局优化.
AFSA-BFGS hybrid algorithm of global optimum for optimization problems
最优化问题全局寻优的AFSA-BFGS混合算法
minimax estimate of location parameter
局部参数的最小最大估计;局部参数的最小最大估计
On the Solving Global Optimization Approach from Local to Global
关于求解全局优化的途径:从局部到全局(英文)
But focusing on how the best produce the best has its limits.
但把目光限于最优如何生产出最优有其局限。
Global Optimality Conditions and Optimization Methods for Quadratic Integer Programming Problems
整数二次规划问题的全局最优性条件及全局最优化方法
Optimization Phase Unwrapping Methods in Interferometric Synthetic Aperture Radar;
各种全局最优INSAR相位解缠算法的研究
One Multiuser Detection Technology with Global Optimality Algorithm;
结合全局最优算法的多用户检测技术
