A Monte-Carlo Algorithm for Probabilistic Propagation in Belief Networks based on Importance Sampling and Stratified Simulation Techniques

A class of Monte Carlo algorithms for probability propagation in belief networks is given. The simulation is based on a two steps procedure. The first one is a node deletion technique to calculate the ’a posteriori’ distribution on a variable, with the particularity that when exact computations a...

সম্পূর্ণ বিবরণ

গ্রন্থ-পঞ্জীর বিবরন
প্রধান লেখক: Hernández, Luis D., Moral, Serafín, Salmerón Cerdán, Antonio
বিন্যাস: info:eu-repo/semantics/article
ভাষা:English
প্রকাশিত: 2017
বিষয়গুলি:
অনলাইন ব্যবহার করুন:http://hdl.handle.net/10835/4899
https://doi.org/10.1016/S0888-613X(97)10004-4