Fractional stochastic resonance multi-parameter adaptive optimization algorithm based on genetic algorithm
| Autor: | Yongjun Zheng, Huang Ming, Wenjun Li, Yi Lu |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Bistability Stochastic resonance Computer science Adaptive optimization Noise intensity Value (computer science) 02 engineering and technology Extension (predicate logic) 020901 industrial engineering & automation Artificial Intelligence Genetic algorithm 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Multi parameter Algorithm Software |
| Zdroj: | Neural Computing and Applications. 32:16807-16818 |
| ISSN: | 1433-3058 0941-0643 |
| Popis: | The output effect of fractional-order stochastic resonance (FOSR) system is affected by many factors such as input system parameters and noise intensity. In practice, many tests are needed to adjust parameters to achieve the optimal effect, and this way of “trial and error” greatly limits the application prospect of FOSR. Based on genetic algorithm, a suitable adaptive function was established to adjust the multiple parameters, including the fractional order, system parameters, and the input noise intensity of the fractional bistable system. Simulation results showed that the algorithm can achieve joint optimization of these parameters. It was proved that this algorithm is conducive to the real-time adaptive adjustment of the FOSR system in practical applications and conducive to the application and extension of FOSR in weak signal detection and other fields. The proposed algorithm has certain practical value. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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