搜索资源列表
FeatureSelection_MachineLearning
- Feature selection methods for machine learning algorithms such as SVR, including one filter-based method (CFS) and two wrapper-based methods (GA and PSO). The gridsearch is for the grid search for the optimal hyperparemeters of SVR. The SVM_CV is for
RoPPlaH-v1.1
- PSO robot path planning, take consideration of the capabilities of the robot, grid based, 2D, intelligent, real-time fast
standard_pso_2011_c
- PSO robot path planning, take consideration of the capabilities of the robot, grid based, 2D, intelligent, real-time fast
micro-grid-capacity-base-on-pso
- 基于PSO算法的微网容量优化配置研究完整matlab程序-PSO algorithm based on optimal allocation of micro-grid capacity matlab program integrity
PSO_for_44_bus
- pso codes for the OPTIMIZATION of the grid 44 buses in IEEE system -pso codes for the OPTIMIZATION of the grid 44 buses in IEEE system
pso-path-planning
- 文件是关于粒子群算法求解路径规划的问题，其中包括栅格障碍物环境的建立，粒子群及其改进算法的仿真程序。-Document on particle swarm algorithm path planning issues, including the establishment, PSO obstacle grid environment and improved algorithm simulation program.
PSO-load-distribution
- 电力系统6台发电机负荷经济分配，采用粒子群算法进行电网经济调度程序-6 generator power system economic load distribution, particle swarm optimization (pso) algorithm is adopted to improve the power grid economic operation procedures
mat-pso-localization-master1
- mat-pso-localization === === === == Mobile robot localization using Particle Swarm Optimization This is a simple localization algorithm for mobile robots that accepts a prebuilt map of the robot s enviornment stored as an occupancy grid
SVM 参数优化
- GA、PSO、GRID 搜索，支持向量机的参数优化方式
pso
- 基于基本粒子群优化算法（PSO）的微电网经济调度研究-Based on the basic particle swarm optimization algorithm (PSO) micro grid economic operation research
priority-based-grid-scheduling-pso-gen
- priority based grid computing scheduling using genetic algorithm and pso
pso-microgrid
- 微电网配置,风机，储能，发电机容量的配置和优化-Micro-grid configuration, fan, energy storage, generator capacity configuration and optimization
2
- Economic Analysis of a Grid-Connected Hybrid Renewable System Supplying CIT Center at Mansoura University-Egypt
pso
- 在微电网中综合考虑经济和环境两个目标，以各微源的运行上下限为约束条件，采用粒子群算法在matlab环境下进行了仿真，最后给出了微网各微源的最优机组组合方式和最佳电能交易计划。(The first establish micro multi-objective energy optimal operation model, taking into account both environmental and economic factors in the model, the operation
PSO_smartgrid
- 使用粒子群算法以经济性为目标对微网系统进行优化(Using particle swarm optimization (PSO) to optimize the micronetwork system with the goal of economy)
Smart-Microgrid-PSO
- 直流微电网采用光伏发电，光伏的最大功率点采用粒子群优化算法实现。(The DC microgrid adopts photovoltaic power generation, and the maximum power point of PV is realized by particle swarm optimization (PSO).)
PSO_BW
- 假设微电网中有风、光、微型燃气轮机、蓄电池，且已知各时段负荷需求；微电网可并网运行，当微网内部发电量较大时，可向电网卖电，而当内部发电不足时，可从大电网购电，价格参考实时电价。考虑各机组运行成本、燃料成本、污染物处理成本、以及买卖电支出或收益。该程序可解决在并网运行模式下，各机组出力如何分配才能达到经济最优的问题。(Suppose there are wind, light, micro gas turbines and batteries in the microgrid, and the l
OPF control of dc grid
- 针对直流电网中的最优潮流问题，提出了一种基于模糊控制理论的自适应粒子群算法，以实现电网兼顾有功网损和电压质量的优化运行。(To solve optimal power flow problem in DC grid, an adaptive particle swarm optimization (PSO) algorithm based on fuzzy control theory is proposed in this paper, and optimal operation consi
micro-grid based on CSO
- 本文分析微网中微电源包括光伏发电、风力发电、微燃机、柴油发电机和燃料电池的电气特性，构建微电网优化运行的模型，以微网的经济成本和环境成本最小为目标函数，充分考虑了电压越限、功率平衡、微电源出力限制等约束条件，应用鸡群算法进行求解。 解决了粒子群算法易早熟、易陷入局部最优解的问题。并通过典型的微网系统进行仿真分析，仿真结果验证了该算法的有效性。(In this paper, the electrical characteristics of micro-power sources in micro
微电网优化调度
- 电网调度，包括风光储配置，目标函数经济性好(Power grid dispatching, including the configuration of wind and solar energy storage, has a good economic objective function)