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Bayesian Simulated Annealing — Global Optimization with Bayesian Priors

Bayesian Simulated Annealing (BSA) mengintegrasikan pengetahuan prior Bayesian tentang lanskap objektif ke dalam proses pencarian simulated annealing. Dengan menyandikan keyakinan tentang kawasan yang menjanjikan sebagai taburan prior dan mengemas kininya seiring kemajuan pencarian, BSA memfokuskan usaha pengiraan pada kawasan berkeupayaan tinggi dalam ruang penyelesaian, mempercepat penumpuan dan meningkatkan kualiti penyelesaian berbanding SA yang tidak dimaklumkan.

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Sumber

  1. Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671–680. DOI: 10.1126/science.220.4598.671
  2. Geman, S., & Geman, D. (1984). Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6(6), 721–741. DOI: 10.1109/TPAMI.1984.4767596

Cara memetik halaman ini

ScholarGate. (2026, June 3). Bayesian Simulated Annealing — Probabilistic global optimization with Bayesian priors on the energy landscape. ScholarGate. https://scholargate.app/ms/simulation/bayesian-simulated-annealing

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ScholarGateBayesian Simulated Annealing (Bayesian Simulated Annealing — Probabilistic global optimization with Bayesian priors on the energy landscape). Dicapai 2026-06-15 daripada https://scholargate.app/ms/simulation/bayesian-simulated-annealing · Set data: https://doi.org/10.5281/zenodo.20539026