- 更多网络例句与惯性群相关的网络例句 [注：此内容来源于网络，仅供参考]
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Key words: artificial intelligence; particle swarm optimization; inertia weight; tangent function; arc tangent function
关键 词：人工智能；粒子群算法；惯性权重；正切函数；反正切函数
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Concerning the disadvantage of the original PSO that is easily trapped in the local optimization and the convergence speed is slow in the evolution later, a particle swarm collaborative optimization algorithm based on velocity angle was proposed. The strategy of inertia weight adjustment was adopted based on cumulative distribution function of Gaussian distribution.
针对PSO存在易陷入局部极值、进化后期收敛速度缓慢的缺点，提出一种基于速度夹角的粒子群协同优化算法，并且引入了一种基于高斯分布的累积分布函数的惯性权重调整策略。
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According to this understanding, this thesis tries to modify PSO algorithm in order to improve its quality of solutions. The main approches include: using uniform design to ensure the uniform distribution of initial particles in the design space; adding mutation operation to increase the diversity of particles; decreasing the maximum velocity limitation and the velocity inertia automatically to balance the local and the global search efforts; developing a new approach to treat the design variables exceeding the bounds; using extensive local searches to escape local minimum. The overall effect of these approaches can yield better results for most test problems.
有鉴於此，本文针对粒子群演化法之流程参考相关文献并稍作改变，使得粒子群演算法在结果的收敛上更具优势，本文的主要改进的方法包括：应用均匀设计的概念使得初始的粒子可以更均匀地分布在空间上；利用突变增加粒子之间的差异性与多样性；利用适当控制的最大速度限制及惯性权重控制，达到区域搜寻与全域搜寻的效果；应用新的边界处理机制处理设计变数超过上、下限的问题；利用区域强化搜寻针对粒子附近地区，再作进一步的搜索以得到更佳之结果；将各种方法综合后配合粒子群演算法使用，可以得到不错的结果。
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In Chapter 1, assuming that the coefficient field κ is perfect and the order of the inertia group is coprime to the characteristic of κ, we prove the existence and the uniqueness of the hyperfocal subalgebra of a source algebra.
在第一章中，假设系数域是完全的；在惯性群的阶与系数域的特征互素的情况下，我们证明了源代数的超聚焦子代数的存在性与唯一性。
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Firstly, we prove the existence and the uniqueness of the hyperfocal subalgebra when the coefficient field is split for a defect pointed group; then, considering the structural pattern of source algebras over arbitrary fields, by means of G-acted groups, we reduce the existence and the uniqueness of the hyperfocal subalgebra over an arbitrary field to the case that the coefficient field is split for a defect pointed group and the inertia group stablizes a hyperfocal subalgebra.
首先我们证明了如果系数域对亏点群是分裂的，则源代数的超聚焦子代数存在且共轭唯一；然后通过考虑任意域上源代数的结构模式，以G-作用群为手段，将超聚焦子代数的存在性和唯一性归结为系数域对亏点群是分裂的情况下惯性群稳定的超聚焦子代数的存在性和唯一性。
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A modified Particle Swarm Optimization algorithm is proposed and used to optimize the sidelobe level of plane arrays, in which special techniques as global best perturbation and jumped inertia weight strategy are adopted. The PSO algorithm is also used to select a better combination of optimal parameters for itself.
摘要该文运用一种改进的粒子群优化算法对不等幅激励的矩形平面阵列天线的最大旁瓣电平进行了优化，采用对全局最优粒子微扰和跳变的惯性权重策略，并使用粒子群算法本身对参数组合进行了优化选择。
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To study the performance of the algorithm, it is tested with a set of 5 benchmark functions and compared with the linear decrease weight particle swarm optimization algorithm.
为了评价其性能，选取了5个基准函数进行测试，并与惯性权重线性递减的粒子群优化算法作了比较。
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A new fuzzy control strategy was presented for the temperature in the tunnel kiln based on adaptive particle swarm optimization algorithms.
针对隧道窑燃烧过程中的大惯性、纯滞后、多变量、时变参数以及工作机理复杂等特征，利用清晰集构造模糊集法确定模糊控制器输入量和输出量的隶属函数，并基于自适应粒子群算法给出了隧道窑新的温度模糊控制策略。
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the effect of inertia weight on particle swarm optimization is studied,on basis of which adopts four kinds of strategies of inertia weight to regulate the speed of a new quantum delta potential well based particle swarm optimization.a faster and more stabile algorithm,found by comparing the performances of four equations regulated the inertia weight,solves 0/1 knapsack problem.the result of experiment shows that the modified algorithm improves the precision of optimal solution and has a faster speed and a higher efficiency in convergence.in a word,choosing a parameter of inertia weight suitably can improve the performance of new qdpso.
摘 要：在研究惯性权重对基本pso算法影响的基础上，根据惯性权重对粒子群算法影响的特点，采用4种惯性权重策略对一种新的具有量子行为的粒子群算法的速度进行调节，比较每种算法的性能，从中找到一种新的性能更好的改进算法，将其用于求解0-1背包问题。实验结果表明较好地选择惯性权重参数对算法的性能有很大提高，该改进算法在求解0-1背包问题中具有高效性，提高了最优解的精度，同时具有较快的收敛速度。
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The effect of iner- tia weight factor on performance of PSO is discussed.The results show that the particle swarm optimiza- tion algorithm with nonlinear inertia weight factor is suitable to solve multivariahle optimum design prob- lem...
结果表明，带动态非线性惯性因子的微粒群算法对求解多变量的干燥优化设计问题具有方法简单、所需微粒群规模小、收敛速度快等特点；采用部分废气循环并进行优化设计对干燥系统的节能具有十分重要的意义，对湿空气出口温度和废气循环比进行优化设计，其年总费用比无废气循环的常规设计节省18.2%，比循环比为0.2时的常规设计节省12.6%。
- 更多网络解释与惯性群相关的网络解释 [注：此内容来源于网络，仅供参考]
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inertia group：惯性群
inertia 惯性 | inertia group 惯性群 | inertial force 惯性力
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inessential mapping：非本质映射
惯性群 inertial group | 非本质映射 inessential mapping | 非本质奇点 inessential singularity
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stellar guidance：恒星导航,天文导引
stellar group 恒星群 | stellar guidance 恒星导航,天文导引 | stellar inertial guidance 天文惯性导航,恒星惯性导航