Recognition of Beef Deterioration Areas Based on Adaptive Optimal Genetic Algorithms
Article
Figures
Metrics
Preview PDF
Reference
Related
Cited by
Materials
Abstract:
To solve the problem of low accuracy and long time of traditional methods for beef deterioration area identification, a method based on adaptive optimization genetic algorithm was investigated. The subset of beef detection spectrum data was used as chromosome, and binary coding was used to calculate individual coding and population initialization. The fitness function was used to optimize crossover and mutation operation, and the individual crossover probability and mutation probability were calculated for different individuals of the population. The final detection spectrum data of beef deterioration area was output. The resultas showed that 40 iterations could conduct beef deterioration area recognition the proposed method. The average recognition accuracy was 95.8%, and the recognition time was 1.7 s. Compared to two traditional methods, the recognition accuracy in this work was improved by 28.72% and 20.34%, respectively, and the recognition time was shortened by 2.09 s and 4.13 s, respectively. The proposed method had the advantages of high recognition rate, short time, high reliability, scientificity and feasibility in identifying beef spoilage areas.
