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Algoritma Genetik Bayesian — Pengoptimuman evolusioner berpandukan model probabilistik

Algoritma Genetik Bayesian (BGA) menggantikan pengendali persilangan dan mutasi tradisional dengan rangkaian Bayesian probabilistik yang dipelajari daripada individu berkefizikalan tinggi yang dipilih. Pada setiap generasi, algoritma membina model grafik struktur penyelesaian yang menjanjikan, kemudian mengambil sampel anak baharu daripada model tersebut, membolehkan carian menangkap dan mengeksploitasi kebergantungan pemboleh ubah yang terlepas oleh GA standard.

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Sumber

  1. Pelikan, M., Goldberg, D. E., & Cantu-Paz, E. (1999). BOA: The Bayesian optimization algorithm. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-1999), pp. 525–532. Morgan Kaufmann. link
  2. Larranaga, P., & Lozano, J. A. (Eds.) (2002). Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation. Kluwer Academic Publishers, Boston. ISBN: 9781461352747

Cara memetik halaman ini

ScholarGate. (2026, June 3). Bayesian Genetic Algorithm — Probabilistic model-guided evolutionary optimization. ScholarGate. https://scholargate.app/ms/simulation/bayesian-genetic-algorithm

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ScholarGateBayesian Genetic Algorithm (Bayesian Genetic Algorithm — Probabilistic model-guided evolutionary optimization). Dicapai 2026-06-15 daripada https://scholargate.app/ms/simulation/bayesian-genetic-algorithm · Set data: https://doi.org/10.5281/zenodo.20539026