搜索资源列表
源代码（vc++）
- 里面装有 5 个小程序，分别是：0-1背包问题、二叉树遍历、链式表的实现、迷宫路径、资源最优配置算法。每个程序都有详细的说明，是我这两个学期所做的实验的一部分。-containing five small programs, namely : 0-2-1 knapsack problem, the binary tree traversal and the chain table and that the realization of the maze path, the optimal res
cccc
- 摘要:提出了一种新型的人工免疫算法用来解决多目标函数优化问题。基于自然免疫系统固有的优良特性对算法进行了设计和分析。 最后,算法对3个较复杂的多目标问题进行了优化,优化结果能很好地覆盖问题的Pareto最优面,并且把算法与某些混合遗传算法进行 了对比实验,表明人工免疫算法在解决多目标优化问题上具有可观的研究前景。 -Abstract:In order to effectively solve multiobjective optimization problems, a novel
optimal_bw_dll
- optimal bandwith mean shift
170
- This paper present a new method to determine the optimal tuning of the PID controller parameter of an AVR system using Modified particle swarm optimization (MPSO) algorithm-This paper present a new method to determine the optimal tuning o
logic2010
- This article presents particle swarm optimization (PSO)-based optimal gain tuning of proportional integral (PI) speed controller in an induction motor (IM) drive (30 hp) with mine hoist load diagram
Power-system-risk-assessment
- 电力系统风险评估方法和应用实例研究,介绍一种新的可用于电力系统规划、设计、运行及维护领域风险评估的方法。该方法强调工程应 用, 探讨电力系统的实际问题。根据规划、运行、维修和资产管理方面的不同要求, 发展特定的概念、针 对性的方法和实施步骤, 如提出元件老化失效模型、共因停运的分离模型及元件组停运模型等新概念。通 过对加拿大某城市电力系统扩建规划实例的分析, 说明如何进行具体工程的可靠性概率评估, 以达到资源 的最佳配置, 使系统风险保持在目标水平。 -Power syste
ppt
- in this power point will contains the detailed explanation for Optimal pricing in cloud cache service
COMPLETE-DOCUMENT
- it will contains the abstract for the implementation of Optimal pricing for a cloud cache service
1
- Learning the Optimal Neighborhood Kernel for Classification
Custom-Evaluation
- 提出一种基于粗糙集与支持向量机的客户动态评估方法。根据客户群特点从当前价值、潜在价值和附加价值三个维度分析并构建客户评估指标，利用指标的年增幅率监测客户价值的变化规律。应用粗糙集布尔推理算法、粒子群算法实现连续属性离散化和知识约简。通过10-重交叉验证和网格搜索技术获取最优惩罚因子与核参数，缩放样本数据集并完成支持向量机一对一分类器的训练与测试。结果表明该评估方法能够实现周期性的客户价值评估与细分，具有很强的泛化能力。- A customer dynamic evaluation method
pso
- pso算法的简单程序，全面的实现了算法的简单快捷性。解决寻找最优问题。-the pso algorithm simple program, comprehensive implementation of the algorithm is simple and quick. The search for optimal problem.
Simulated-Annealing
- 由于K-means 聚类方法对遥感图像进行分类时，对训练样本的选取依赖性很大，容易陷入局部最优的陷阱的情况，本文提出利用模拟退化算法对K-means 的聚类进行优化以获得 全局最优解的分类新方案。并以多波段影像为例进行验证分析，结果表明该方法可行，收敛 结果优于K-means 聚类算法，分类精度相对传统的K-means 算法更高。-Because K-means clustering classification depend on the training sample selecti
Nonlinear-Optimal-Predictive
- 关于静止同步无功功率补偿器的非线性预测控制-Nonlinear Optimal Predictive Controller for Static Synchronous Compensator (STATCOM)
PIDyichuansuanfa
- 遗传算法入门，从生物学角度到电子学角度，清楚阐述遗传算法求出最优值的问题答案。其中包含一个基于ARM控制电压的算法代码。-Genetic algorithms entry, from a biological point of view to the electronics point of view, clearly describes the genetic algorithm to derive the optimal value of the answer. Which contains
NVME
- • Queues allocated per core via local memory • IOs submitted on optimal queue for CPU • MSIX vectors mapped to NUMA optimized Queue pair ‘All or Nothing’ optimization, each core gets a queue and a vector or driver reverts to singe queue pair
OMP
- The problem of optimal approximation of members of a vector space by a linear combination of members of a large overcomplete library of vectors is of importance in many areas including image and video coding, image analysis, control theory, a
optimal
- optimal location of the facts devices in the power system for reactive power compensation and the voltage instability
Power-Optimization
- 电力系统无功优化对确保电力系统优化运行具有重要作用,它直接关系到电力系统运行的安全性与经济性。在已有研究成果的基础上,提出了单目标／多目标的导向搜索算法与单目标／多目标的动态多群体自适应差分进化算法,对电力系统静态单目标无功优化、静态多目标无功优化、动态单目标无功优化、动态多目标无功优化、典型函数优化等问题进行了深入的研究和探讨。-Reactive power optimization to ensure the optimal operation of the power system pla
Coordination-and-Optimization
- 将网损价格因子和网损协调系数引入目标函数,建立了改进直流潮流模型,实现了负荷在机组间的最优分配 利用交流潮流方法计算系统实际网损,并利用增量直流潮流模型将网损在机组间进行合理分摊 最后利用交直流迭代思想修正网损价格因子和网损协调系数以优化网损分配方案。IEEE14节点和IEEE118节点算例验证了该方法的可行性,算例结果充分逼近了交流最优潮流的计算结果,符合实际系统运行状况。-The net loss and net loss of coordination price factor intro
A-Robust-Denoising-Algorithm
- In this paper, a robust DWPT based adaptive bock algorithm with modified threshold for denoising the sounds of musical instruments is proposed. The signal is first segmented into multiple blocks depending upon the minimum mean square criteria in each