Parameter estimation of S-shaped growth model: A modified particle swarm algorithm

2012 ◽  
Vol 17 (2) ◽  
pp. 137-143
Author(s):  
Xing Xu ◽  
Bo Wei ◽  
Yu Wu ◽  
Bingxiang Liu ◽  
Yuanxiang Li
Keyword(s):  
Parameter Estimation ◽  
Growth Model ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Swarm Algorithm

GPU-Based PSO Application in Multiuser Detection and Trajectory Parameter Estimation

2013 ◽  
Vol 340 ◽  
pp. 829-832
Author(s):  
Lei Sun ◽  
Han Tao Zhang ◽  
Xiao Ping Zhou
Keyword(s):  
Parameter Estimation ◽  
Real Time ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
System Capacity ◽  
Particle Swarm Algorithm ◽  
Processing Unit ◽  
Trajectory Parameter ◽  
Multiuser Detector ◽  
Swarm Algorithm

The parallel character of particle swarm algorithm (PSO) and the Graphic Processing Unit (GPU) technology of Compute United Device Architecture (CUDA) from NVIDIA are analyzed. Two methods of the realization of PSO based on GPU are discussed. One method is using the module of open source particle swarm algorithm supporting the GPU, with the application of multiuser detector (MUD). The other method is using the module of MATLAB supporting the GPU with the application of the moving parameter estimation. The test results show that the PSO algorithm based on GPU technology can significantly improve the speed of system capacity, to solve the problem of multi-dimensional global optimization, with the poor real-time performance. It can be widely used in the project of high real-time requirements.

Dynamic simulation of wind field in three-dimensional display space considering particle swarm algorithm fuzzy logic

2021 ◽  
pp. 1-6
Author(s):  
Honglei Xu ◽  
Linhuan Wang
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Simulation ◽  
Wind Field ◽  
Three Dimensional ◽  
Measurement Data ◽  
Particle Swarm ◽  
Particle Swarm Algorithm ◽  
Three Dimensional Display ◽  
Swarm Algorithm ◽  
Synchronous Measurement

In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude.

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