منابع مشابه
Bayesian Belief Network Simulation
A Bayesain belief network is a graphical representation of the underlying probabilistic relationships of a complex system. These networks are used for reasoning with uncertainty, such as in decision support systems. This requires probabilistic inference with Bayesian belief networks. Simulation schemes for probabilistic inference with Bayesian belief networks offer many advantages over exact in...
متن کاملGreen Supply Chain Risk Network Management and Performance Analysis: Bayesian Belief Network Modeling
With the increase in environmental awareness, competitions and government policies, implementation of green supply chain management activities to sustain production and conserve resources is becoming more necessary for different organizations. However, it is difficult to successfully implement green supply chain (GSC) activities because of the risks involved. These risks alongside their resourc...
متن کاملProperties of Bayesian Belief Network Learning Algorithms
In this paper the behavior of various be lief network learning algorithms is stud ied. Selecting belief networks with cer tain minimallity properties turns out to be NP-hard, which justifies the use of search heuristics. Search heuristics based on the Bayesian measure of Cooper and Her skovits and a minimum description length (MDL) measure are compared with re spect to their properties for...
متن کاملAlgorithms for Bayesian belief-network precomputation.
Bayesian belief networks provide an intuitive and concise means of representing probabilistic relationships among the variables in expert systems. A major drawback to this methodology is its computational complexity. We present an introduction to belief networks, and describe methods for precomputing, or caching, part of a belief network based on metrics of probability and expected utility. The...
متن کاملBayesian Quantized Network Coding via Belief Propagation
In this paper, we propose an alternative for routing based packet forwarding, which uses network coding to increase transmission efficiency, in terms of both compression and error resilience. This non-adaptive encoding is called quantized network coding, which involves random linear mapping in the real field, followed by quantization to cope with the finite capacity of the links. At the gateway...
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ژورنال
عنوان ژورنال: Journal of Clinical Pathology
سال: 1996
ISSN: 0021-9746
DOI: 10.1136/jcp.49.10.864-b