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Simulation of an NSGA-III Based Fireball Inner-Temperature-Field Reconstructive Method
- Source :
- IEEE Access, Vol 8, Pp 43908-43919 (2020)
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- For the inner-temperature-field reconstruction of a fireball, a detecting method was proposed, using multi-channel visible spectral remote sensing theory. In our proposed method, the reconstructive algorithm based on multi-channel-detection was considered as a multi-objective optimization problem (MOOP), and a fast non-dominated sorting genetic algorithm based on reference-point strategy (NSGA-III) was employed as the solution of this problem. Besides, a so-called ambient pressure operator, based on the unique detecting model, was proposed and employed during the iteration process, for dynamic genetic parameter adjustment. To verify some performance of our proposed method, several numerical reconstructive simulations were carried out, from simple GA to NSGA-III, using several artificial 2-D virtual data, with different kinds of crossover and mutation functions. The simulation results show that, limited to our problems, the NSGA-III can effectively reconstruct different 2-D data, by a fixed crossover rate and a dynamic mutation rate under the proposed ambient pressure operator and an adaptive mutation rate function. The algorithm, limited to the field-reconstruction, also performs well on stability, but still has some deficiencies to be optimized.
- Subjects :
- Optimization problem
General Computer Science
Computer science
Crossover
General Engineering
Stability (learning theory)
Sorting
NSGA-III
Field reconstruction
Operator (computer programming)
Adaptive mutation
Genetic algorithm
Mutation (genetic algorithm)
General Materials Science
MOOP
lcsh:Electrical engineering. Electronics. Nuclear engineering
Algorithm
lcsh:TK1-9971
ambient pressure operator
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....e63467ed9777ee4a771e9b7ef40e2766