Multi-objective decision engine parameter optimization method based on multi-objective quantum ant colony algorithm

A technology of multi-objective decision-making and optimization method, which is applied in the field of multi-objective decision-making engine parameter optimization, and can solve problems such as finding the optimal solution

Inactive Publication Date: 2013-09-25
HARBIN ENG UNIV
View PDF3 Cites 25 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Cognitive radio multi-objective decision engine technology can be regarded as a discrete multi-objective combination o

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
  • Multi-objective decision engine parameter optimization method based on multi-objective quantum ant colony algorithm
  • Multi-objective decision engine parameter optimization method based on multi-objective quantum ant colony algorithm
  • Multi-objective decision engine parameter optimization method based on multi-objective quantum ant colony algorithm

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0046] The present invention will be further described below in conjunction with the drawings:

[0047] Aiming at the shortcomings of the linear weighting method for the decision engine of the existing cognitive radio system, the present invention proposes a multi-objective cognitive engine parameter optimization method that simultaneously considers the goals of minimizing transmit power, minimizing bit error rate, and maximizing data rate. . This method first proposes quantum pheromone, and then proposes a multi-objective quantum ant colony optimization method, and is based on non-dominated path sorting, so as to obtain a Pareto front-end path with a uniformly distributed non-dominated path set. In actual engineering applications, different weights can be selected for the three targets according to the actual communication environment and requirements, and the most appropriate path can be selected from the Pareto front-end path set. Therefore, the method proposed by the present...

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 multi-objective decision engine parameter optimization method capable of enabling the minimum transmitting power, the minimum bit error rate and the maximum data rate to a cognitive radio system to be optimal at the same time. The method comprises steps of establishing a multi-objective decision engine model, calculating a multi-objective quantum ant colony algorithm path initial value, initializing a quantum information element of a multi-objective quantum ant colony algorithm, carrying out non dominated path sorting and the calculation of path congestion, sorting paths with the same non dominated path sorting rank, selecting a path with a non dominated path sorting rank of 1 and adding the path into an elite path set, calculating the path congestion, and selecting a path mapping to obtain the needed system parameter. According to the method, a discrete multiple-objective decision engine parameter optimization problem is solved, and the multi-objective quantum ant colony algorithm with non dominated path sorting is designed as a solution strategy, and the convergence precision is raised. The minimum transmitting power, the minimum bit error rate and the maximum data rate are considered at the same time, and the applicability is broadened.

Description

technical field [0001] The invention relates to a multi-objective decision-making engine parameter optimization method based on a multi-objective quantum ant colony algorithm, which simultaneously enables a cognitive radio system to minimize transmission power, minimize a bit error rate, and maximize a data rate. Background technique [0002] With the rapid development of wireless communication, the serious shortage of limited spectrum resources has become increasingly prominent, which has become an obstacle restricting the sustainable development of wireless communication. Cognitive radio is a new technology proposed in recent years to solve the phenomenon of spectrum resource shortage. This technology enables cognitive users to use idle spectrum without interfering with licensed users and other cognitive users, making full use of spectrum resources, improving system capacity and spectrum utilization, and alleviating the shortage of spectrum resources and the rapid growth. ...

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
IPC IPC(8): G06N3/00
Inventor 高洪元李晨琬赵宇宁刁鸣
Owner HARBIN ENG 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