资源列表
PSO-PID参数
- 利用标准粒子群算法优化PID参数，用以控制直流电机模型(The standard particle swarm optimization (PSO) algorithm is used to optimize the PID parameters to control the DC motor model)
StewardPlatformSolver
- 本matlab程序仿真了6自由度Stewart平台,得到了正反解,并提供了可视化的GUI界面,可作为求解工作空间的参考,其中正解方法参考自以下论文: Lee, Tae-Young, and Jae-Kyung Shim. "Forward kinematics of the general 6–6 Stewart platform using algebraic elimination." Mechanism and Machine Theory 36.9 (2001):
应用禁忌搜索算法解决0-1背包问题
- 利用禁忌搜索算法求解0-1背包问题。禁忌搜索算法相比其他搜索算法更优，设置藐视规则来避免陷入局部最优解。(Solve 0-1 Knapsack Problem based on Tabu search. The tabu search algorithm is superior to other search algorithms and sets contempt rules to avoid falling into local optimal solutions.)
动态重构
- 基于遗传算法配电网重构的解决经济问题的一份程序，很完整，值得拥有(A procedure for solving economic problems based on genetic algorithm power distribution network reconstruction is very complete and worth having)
9927438PV
- 建立包含直驱型风力发电机、单级式光伏发电系统和储能蓄电池的风能与光伏混合微电网模型。混合微电网在并网运行时，通过储能蓄电池平滑风能和光伏电源的输出功率波动，维持公共连接点电压。(A wind power and photovoltaic hybrid microgrid model including direct drive wind turbine, single-stage photovoltaic power generation system and energy storage ba
新建文件夹
- 复合电源电动汽车能量管理策略，动力电池—超级电容的复合电源系统的某微型纯电动汽车为研究对象，提出了一种基于随机动态规划的超级电容和动力电池能量分配的优化控制策略。(Energy management strategy of composite power electric vehicle)
PSO
- 微电网多目标调度，运用改进的多目标粒子群算法进行计算，里面包含经济等三个目标函数设置((Smart Microgrid PSO, micro sources: photovoltaic, wind turbines, generators, energy storage, etc.))
matlab有限元计算程序--平板小孔应力集中问题
- 用于有限元的matlab计算，matlab有限元集中问题(Matlab calculation for finite element)
WOAlssvm
- 鲸鱼算法改进优化，结合最小二乘支持向量机，(Whale algorithm optimization)
PWE
- matlab源程序 用于计算声子晶体的能带结构(Matlab source program The band structure for the calculation of phononic crystals)
pso-svm电力负荷预测
- 电力负荷预测是电力系统规划的重要组成部分，也是电力系统经济运行的基础，其对电力系统规划和运行都极其重要。利用粒子群算法优化支持向量机更加高效准确预测电力负荷。(The power load forecasting is an important part of the power system planning, and it is also the basis of the economic operation of the power system. It is very important
pro
- 基于matlab/simulink的5机14节点和3机9节点仿真(base on matlab/simulink 5 machine 14 node and 3 machine 9 node simulation)