A parallel hybrid genetic algorithm simulated annealing approach to finding most probable explanations on Bayesian belief networks

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 1, Issue , 1997, Pages 450-455

  Abdelbar, Ashraf M ^a   Hedetniemi, Sandra M ^b  

^a The American University in Cairo   (Egypt)

^b Clemson University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ASSIGNMENT PROBLEMS; KNOWLEDGE STRUCTURES; MAXIMUM A POSTERIORI; MOST PROBABLE EXPLANATION; NETWORK VARIABLES; PARALLEL HYBRID-GENETIC ALGORITHMS; PARALLEL PROCESSING; REASONING UNDER UNCERTAINTY;

DECISION THEORY; GENETIC ALGORITHMS; NEURAL NETWORKS; SIMULATED ANNEALING; COMPUTATIONAL COMPLEXITY; KNOWLEDGE BASED SYSTEMS; PARALLEL ALGORITHMS; PARALLEL PROCESSING SYSTEMS; PROBABILITY; PROBLEM SOLVING;

BAYESIAN NETWORKS; NEURAL NETWORKS;

BAYESIAN BELIEF NETWORKS; MAXIMUM A POSTERIORI (MAP) ASSIGNMENT PROBLEM; MOST PROBABLE EXPLANATION (MPE) PROBLEM;

EID: 0030658514     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNN.1997.611710     Document Type: Conference Paper

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