Particle swarm positioning algorithm based on adaptive differential

An adaptive differential and positioning algorithm technology, applied in electrical components, wireless communication, network topology, etc., can solve the problems of slow particle swarm positioning convergence, unstable positioning, etc., to enhance exploration capabilities, increase hardware costs, and speed up convergence. effect of speed

Inactive Publication Date: 2016-04-20
JIANGNAN UNIV
View PDF5 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0015] The purpose of this invention is to solve the problem of slow convergence and unstable positioning based on particle swarm positioning, and propose a particle swarm positioning algorithm based on adaptive difference

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Particle swarm positioning algorithm based on adaptive differential
  • Particle swarm positioning algorithm based on adaptive differential
  • Particle swarm positioning algorithm based on adaptive differential

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0035] The particle swarm localization algorithm based on adaptive difference mainly includes differential mutation particle swarm, selection operator, and particle swarm algorithm and difference algorithm to jointly search for local optimal solutions and compare fitness values. In the present invention, 100m×100m is used as the experimental simulation area, and the communication between all nodes in the simulation area is normal, and the communication radius is 30m; the population size is NP=30, and the maximum number of iterations is g max = 60, the maximum speed v max =10, initial inertia weight w max = 0.8, the final weight w min =0.1,c 1 =c 2 = 2, all simulation tests are carried out 500 times, using the average positioning error to judge the positioning accuracy of the algorithm:

[0036] A V E = Σ i = 1 ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a particle swarm positioning algorithm based on adaptive differential. The particle swarm positioning algorithm mainly comprises relation establishment between signal intensities and distances, least squares algorithm position computation, and a new search method, and includes receiving the distance information of an anchor node by using a unknown node, computing a position by using a least squares algorithm, generating a new swarm by using an improved adaptive differential algorithm, performing local search by using a particle swarm algorithm and a new mutation strategy, comparing with adaptive values and repeatedly performing iteration in order to achieve asymptotic convergence, and finally obtaining the position of the unknown node. The diversity of the swarms generated by the new differential algorithm is guaranteed and it increases rate of convergence and positioning precision to perform the local search by the combination of the particle swarm algorithm and the differential algorithm.

Description

technical field [0001] The invention belongs to the technical field of wireless sensor networks, and relates to a particle swarm positioning algorithm based on adaptive difference. Background technique [0002] With the in-depth research and application of the Internet of Things, wireless sensor networks have played a key role in promoting it. Wireless sensor networks have many applications in military and civilian fields, including environmental monitoring, website security, medical diagnosis, battlefield surveillance, disaster relief, and assisted living. Many applications in life are related to location. Wireless sensor networks have great advantages in indoor positioning due to their easy deployment, high scalability, and low cost. [0003] Positioning technology is one of the main supporting technologies of wireless sensor networks, and has received extensive attention from researchers. The existing wireless sensor network positioning can be mainly divided into rangin...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): H04W64/00H04W84/18
CPCH04W64/00H04W84/18
Inventor 卢先领夏文瑞
Owner JIANGNAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap