2) improved particle filter
改进粒子滤波
1.
Based on the Bayes principle,an improved particle filter(IPF) algorithm was proposed,which is adapted for the gas pollution source localization using WSN.
基于贝叶斯原理,提出一种适用于WSN的气体污染源定位算法——改进粒子滤波(IPF)算法。
3) modified particle swarm optimization
改进粒子群算法
1.
Scheme of sliding mode control based on modified particle swarm optimization
基于改进粒子群算法的滑模控制方案
2.
A modified particle swarm optimization (MPSO) algorithm for bidding management in power pool environment is presented, it remedies the defects in basic particle swarm optimization (PSO) such as low convergence accuracy and easy to fall in with premature convergence.
提出了一种新的用于求解电力库模式下竞价管理问题的改进粒子群算法,改善了基本粒子群优化算法收敛精度不高且易陷入局部极值的缺点。
3.
An approach to solve the problem about the optimization of block erection sequence on the berth using PSO is proposed and a modified particle swarm optimization is designed on the basis of analysis about the basic principle of PSO.
本文以船台吊装顺序优化为研究对象,以粒子群优化算法(PSO),资源受限项目调度问题(RCPSP)为理论依据,主要做了如下的研究:分析了船台吊装技术及船台调度问题的研究现状,给出了船台吊装顺序优化系统,阐述了系统各个部分的功能和实现方法;提出采用粒子群算法求解船台吊装顺序优化问题,通过分析PSO的基本原理,对算法进行改进;采用带约束有向图搜索算法完成了船台吊装顺序规划,并对船台吊装网络图的构建方法进行了研究;将RCPSP问题应用于船台吊装顺序优化中,构建了以最短工期为目标的船台吊装顺序多资源优化模型,并结合实际吊装过程,构建了突发情况下的船台吊装顺序优化模型;给出了改进粒子群算法求解船台吊装顺序优化问题的实现方法,并使用典型RCPSP问题算例验证实现方法的正确性。
4) IPSO
改进粒子群算法
1.
Research on the Function of Reservoir Long-term Operation Based on Improved Particle Swarm Optimization(IPSO);
基于改进粒子群算法的水库中长期调度函数研究
2.
This paper proposes an Improve Particle Swarm Optimization(IPSO) which is applied to this problem.
输电网扩展规划是一个非常复杂的大规模组合优化问题,提出了一种改进粒子群算法求解此类优化问题。
3.
The efforts suggest that the IPSO-BP neural network model has a strong generalization ability,and it can perfectly express the flux and torque characteristics of SRG.
该方法利用了BP神经网络较强的非线性处理能力和逼近能力,改进粒子群算法的引入克服了BP神经网络容易陷入局部最优及初值敏感的缺点。
5) improved particle swarm optimization algorithm
改进粒子群算法
1.
So An optimal selection approach of SVR parameters was put forward based on improved particle swarm optimization algorithm.
因此提出了基于改进粒子群算法的SVR参数优化选择方法。
2.
To intelligent vehicle steering system which are of characteristics of complex,nonlinearity and time-variation,a self-adaptive PID control was proposed based on improved particle swarm optimization algorithm(IPSO),which acquired on-line tuning information of PID parameters,and the self-tuning of controller parameters was implemented by IPSO,and the intelligent control of system was achieved.
针对智能车辆转向系统的复杂,非线性和时变性,提出了基于改进粒子群算法的自适应PID控制,在该控制系统结构中,采用改进粒子群算法获得PID参数在线调整的信息,完成PID控制器参数的在线自整定,实现智能车辆转向的智能控制。
6) improved particle swarm optimization
改进粒子群算法
1.
A method for regional real-time var/voltage optimization control based on improved particle swarm optimization algorithm is proposed on the model of real-time optimization.
在建立无功/电压实时优化控制模型的基础上,提出了一种基于改进粒子群算法的地区电网无功/电压实时优化控制实现方法。
2.
The improved particle swarm optimization algorithm is used in the economic load dispatch(ELD) problems of power system.
为解决电力系统中的经济负荷分配问题,将改进粒子群算法用于其中。
补充资料：初级粒子和原级粒子
分子式：
CAS号：
性质：又称初级粒子和原级粒子。利用各种化学反应方法得到的最初粒子(晶粒)。一次粒子的大小约为0.005～1μm，比筛分的极限小得多，在介质中有相当高的稳定性。
CAS号：
性质：又称初级粒子和原级粒子。利用各种化学反应方法得到的最初粒子(晶粒)。一次粒子的大小约为0.005～1μm，比筛分的极限小得多，在介质中有相当高的稳定性。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条