Sequential test optimization method based on multi-objective genetic programming algorithm
A technology of multi-objective genetic and optimization method, applied in the field of sequential test optimization based on multi-objective genetic programming algorithm, can solve problems such as unsuitable systems
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment
[0106] In order to better illustrate the technical effect of the present invention, a specific embodiment is used for simulation verification. Table 1 is the failure-test dependency matrix of the electronic system in this example, including failure probability and test cost.
[0107]
[0108] Table 1
[0109] The conditions for this experiment verification are as follows: CPU: Pentium G3250; operating system: Windows 7; programming language: JAVA. Genetic programming related parameters: population size: 100; evolution algebra: 100 crossover rate: 0.8; mutation rate 0.05. The test indicators used are test cost and test time, and the threshold of congestion distance δ share = 0.3.
[0110] The sequential test optimization is carried out by using the present invention, and 12 Pareto optimal solutions are obtained. Table 2 is a list of test costs and test time for the Pareto optimal solution in this embodiment.
[0111] testing time testing fee 3.303 12.48...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com