An adaptive differential evolution algorithm witha bound adjustment strategy for solving nonlinear parameter identification problems

• Autorzy: Wongsa Watchara , Puphasuk Pikul , Wetweerapong Jeerayut

Identyfikatory

DOI

10.35784/iapgos.5684

Warianty tytułu

PL

Adaptacyjny różniczkowy algorytmewolucyjny ze strategią dostosowywania granic do rozwiązywania nieliniowych problemów identyfikacji parametrów

• Języki publikacji: EN

Abstrakty

EN

Real-world parameter identification problems require determining the bounds that cover the unknown solutions. This paper presents an adaptive differential evolution algorithm with a bound adjustment strategy (ADEBAS) for solving nonlinear parameter identification problems. The adjustment strategy detects the parameter-bound violations of mutant vectors during the evolution process and gradually extends the bounds. The algorithm adaptively uses two mutation strategies and two ranges of crossover rate to balance the population diversity and convergence speed. Experimental results show that ADEBAS can solve 24 nonlinear regression tasks from the National Institute of Standards and Technology benchmark with accurate estimation and reliability. It also outperforms the compared methods on real-world parameter identification problems.

PL

Problemy identyfikacji parametrów w świecie rzeczywistym wymagają określenia granic, które pokrywają nieznane rozwiązania. W artykule przedstawiono adaptacyjny różniczkowy algorytm ewolucyjny ze strategią dostosowywania granic (ADEBAS) do rozwiązywania nieliniowych problemów identyfikacji parametrów. Strategia dostosowywania wykrywa naruszenia granic parametrów zmutowanych wektorów podczas procesu ewolucji i stopniowo rozszerza granice. Algorytm adaptacyjnie wykorzystuje dwie strategie mutacji i dwa zakresy szybkości krzyżowania, aby zrównoważyć różnorodność populacji i szybkość zbieżności. Wyniki eksperymentów pokazują, że ADEBAS może rozwiązać 24 zadania regresji nieliniowej z benchmarku National Institute of Standards and Technology z dokładnym oszacowaniem i niezawodnością. Przewyższa również porównywane metody w rzeczywistych problemach identyfikacji parametrów.

Słowa kluczowe

EN

parameter identification; differential evolution algorithm; bound adjustment strategy

PL

identyfikacja parametrów; algorytm ewolucji różnicowej; strategia dopasowania powiązanego

• Wydawca: Wydawnictwo Politechniki Lubelskiej
• Czasopismo: Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
• Rocznik: 2024
• Tom: T. 14, nr 2
• Strony: 119--126
• Opis fizyczny: Bibliogr. 28 poz., wykr.

Twórcy

autor

Wongsa Watchara

• Khon Kaen University, Faculty of Science, Department of Mathematics, Khon Kaen, Thailand

• https://orcid.org/0000-0001-6320-149x

autor

Puphasuk Pikul

• Khon Kaen University, Faculty of Science, Department of Mathematics, Khon Kaen, Thailand

• https://orcid.org/0000-0001-9069-1703

autor

Wetweerapong Jeerayut

• Khon Kaen University, Faculty of Science, Department of Mathematics, Khon Kaen, Thailand

• https://orcid.org/0000-0001-5053-3989

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