
[数] 优化算法
Design of experiment and global optimization algorithm are integrated in the system to enhance optimization robustness and accelerate convergence.
优化设计采用试验设计与全局优化算法相结合以提高设计的稳健性,加速收敛。
The standard particle swarm optimization algorithm as a random global search algorithm, because of its rapid propagation in populations, easily into the local optimal solution.
标准的粒子群优化算法作为一种随机全局搜索算法,因其在种群中传播速度过快,易陷入局部最优解。
In this paper, we apply WAGA to optimize soft morphological filters and study the performance of optimization algorithm with various noise percentages under MAE or MSE error criteria.
本文应用WAGA优化柔性形态滤波器,并研究了在不同噪声比例和最小平均绝对误差(MAE)、最小均方误差(MSE)准则下优化算法的性能。
The iterative optimization algorithm is an important method in pattern recognition.
迭代最优化算法是模式识别中一种重要方法。
But too complex and aggressive optimization algorithm will cost much compilation time and resources.
而复杂的编译优化算法需要耗费大量的编译时间和资源。
A redundancy optimization model is established. A new method of system reliability grounded in particle swarm optimization algorithm, which combines with idea of genetic algorithm, is put forward.
建立了可靠性冗余优化模型,提出了一种基于粒子群优化算法的可靠性优化的新方法,该方法结合了遗传算法的思想。
A particle swarm optimization algorithm source code, this is a VB source languages, it is practical.
一种粒子群优化算法源程序,这是一个VB语言编制的源程序,很实用。
In this paper are presented the basic conception of mutual information, the transform model, the insert value algorithm, the optimization algorithm and the strategy in computing mutual information.
详细地介绍了互信息的基本概念、归一化互信息、互信息计算中常用的变换模型、插值方法、优化算法及提高配准速度策略等。
For satellite data transmission scheduling problem(SDTSP) restrained with time windows and resources, ant colony optimization algorithm based on solution construction graph model is proposed.
针对具有时间窗口和数传资源限制卫星数传调度问题,提出了基于解构造图模型的蚁群优化算法。
Immune Algorithm is an optimization algorithm based on immune system of organism in nature, now it is a new development direction in multi-object of mechanical optimization design.
免疫算法是一种基于自然界生物体免疫系统的优化算法,是目前机械多目标优化设计中的一个新的研究方向。
The paper introduces main features about the toolbox and give optimization algorithm under constrain condition.
介绍了工具箱的主要特点,并给出了在约束条件下的优化算法。
Chaos optimization algorithm, which combines chaos carrier wave with simulated annealing algorithm improves system optimization speed.
混沌优化算法将混沌载波和模拟退火策略结合加快了寻优速度。
Intelligence optimization algorithm is a new type optimization algorithm.
群智能优化算法是一种新型的优化算法。
A new heuristic optimization algorithm for solving the problem was presented.
提出了解决这类问题的新的启发式优化算法。
The global optimization algorithm for multimodal functions of both continuous and discrete variables are stu***d in the first part.
首先,重点讨论了适合于连续变量及离散变量多极值点目标函数的全局优化算法。
Competitive algorithm is a parallel heuristic optimization algorithm, its searching mechanism simulate the pursue motive to the support-rate in the electing activity.
竞选算法是一种具有并行能力的启发式优化算法,其搜索机制模拟竞选活动中对支持率的追求动机。
Experimental results show that the algorithm is an efficient global optimization algorithm.
实验结果表明,该算法是一种快速有效的全局优化算法。
Subsequently, modeling means, optimization algorithm and its status in detail for the mission planning system are analyzed.
然后,详细分析了任务规划系统的建模技术及其优化算法的研究现状。
To further improve the performances of infinite impulse response(IIR) digital filters, a new approach based on the seeker optimization algorithm(SOA) was proposed for IIR digital filter design.
为进一步提高无限冲击响应(IIR)数字滤波器的性能,提出了一种基于搜寻者优化算法(SOA)的IIR数字滤波器设计方法。
It is compared with basic particle swarm optimization algorithm and genetic algorithm. Results prove that this algorithm is effective.
经过实验仿真,与基本微粒群优化算法、遗传算法进行比较,证明了该算法的有效性。
To improve the efficiency of disk scheduling, this paper proposed an optimization algorithm of disk scheduling based on the Average Seek Time(AST).
针对如何提高磁盘调度效率的问题,提出了一种基于平均寻道时间(AST)的磁盘调度优化算法。
For parameter estimation of nonlinear system, this paper proposed a hybrid optimization algorithm integrating parallel chaotic search algorithm(PCS)with pattern search method(PS).
提出了一种并行混沌搜索结合模式搜索法的混合优化算法,并应用于非线性系统参数估计。
The chaotic time series optimization algorithm is applied in the analysis of the pumping experiment data to optimize the function of aquifer parameters to estimate the parameters.
以泰斯公式为例,将混沌序列优化算法应用于求解分析抽水试验资料,确定含水层参数的函数优化问题。
In this dissertation, Membrane optimization algorithm is applied in finding sequences suitable for reliable DNA computing in this thesis, a new method of DNA sequence design is pu.
本文采用膜优化算法优化DNA计算编码序列,提出了一类求解DNA编码问题的新方法,扩展了膜计算的应用领域。
This paper researches the application of the stochastic parallel gra***nt descent(SPGD)optimization algorithm on the beam cleanup system.
就随机并行梯度下降(SPGD)最优化算法在光束净化系统中的应用展开研究。
A wide range of papers related to the life system modeling and simulation, artificial intelligence, calculation and optimization algorithm and its application.
一个广泛的生命系统建模与仿真,人工智能,计算和优化算法及其应用有关的论文。
The simulation result shows that ACNN is a global optimization algorithm which can effectively solve four-coloring map problem.
仿真结果表明,这是一个能有效求解四色图着色问题的全局最优化算法。
Developed the research which coupling ANSYS finite element analysis and Fuzzy Genetic optimization Algorithm.
开展了ANSYS有限元分析与模糊遗传优化算法的耦合研究。
Structure of multi-layer feedback forward neural network is optimized using improved particle swarm optimization algorithm. Learning quality and training speed of the neural network are improved.
提出的自适应粒子群优化算法,用于优化多层前馈神经网络的拓扑结构,提高了神经网络的学习质量和速度。
优化算法(Optimization Algorithm) 是指一类用于在给定约束条件下,寻找某个目标函数(Objective Function)最优解(最大值或最小值)的计算方法或步骤序列。其核心目标是在可行的解空间中高效、准确地定位最佳决策方案。
梯度下降法(Gradient Descent)
适用于目标函数可微的场景。通过计算函数在当前点的梯度(指向函数值增长最快的方向),沿负梯度方向迭代更新变量以逐步逼近局部最小值。广泛应用于训练神经网络(如反向传播算法)。其更新公式为:
$$ theta_{t+1} = theta_t - eta abla f(theta_t) $$
其中 $theta$ 为参数,$eta$ 为学习率,$ abla f$ 为梯度。来源:经典数值优化教材(如 Nocedal & Wright, Numerical Optimization)。
进化算法(Evolutionary Algorithms)
模拟生物进化机制(选择、交叉、变异),维护一个候选解群体,通过多代演化逐步优化。代表性算法包括遗传算法(Genetic Algorithms)。这类算法擅长处理非凸、非线性或离散优化问题,对目标函数连续性要求低。来源:IEEE Computational Intelligence Society相关研究。
启发式与元启发式算法
如模拟退火(Simulated Annealing)、蚁群优化(Ant Colony Optimization)。通过引入随机性和特定规则(如退火中的温度下降)探索解空间,避免陷入局部最优,常用于组合优化问题(如旅行商问题)。来源:《Operations Research》期刊相关论文。
scipy.optimize
模块)优化算法(Optimization Algorithm)是用于在给定约束条件下寻找目标函数最优解(最大值或最小值)的数学方法或计算步骤。它在科学、工程、经济学和人工智能等领域广泛应用。以下是详细解释:
梯度下降法(Gradient Descent)
通过迭代调整参数,沿目标函数梯度反方向更新以最小化函数值。适用于连续可微问题,但可能陷入局部最优。
遗传算法(Genetic Algorithm)
模拟生物进化过程,通过选择、交叉和变异操作搜索全局最优解。适合复杂、非凸问题,但计算成本较高。
粒子群优化(Particle Swarm Optimization, PSO)
模拟鸟群觅食行为,粒子通过跟踪个体和群体最优位置更新自身状态。常用于多目标优化。
Adam(Adaptive Moment Estimation)
结合动量法和自适应学习率的深度学习优化器,能高效处理高维参数和非平稳目标函数。
梯度下降的更新公式为:
$$
theta_{t+1} = theta_t - eta cdot
abla_theta J(theta)
$$
其中,$theta$ 是参数,$eta$ 为学习率,$
abla_theta J(theta)$ 是目标函数关于参数的梯度。
如需进一步学习,可参考经典教材《Numerical Optimization》或在线课程(如Coursera的《Machine Learning》)。
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