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31. According to Bayesian theory and Bayes Factor, the posterior probability of the calculation sample belonging to a model is calculated.

32. However, reasoning on student model is a NP hard question in fact, since undirected loops are embedded in the Bayesian student model.

33. Under the assumption of security dependence relation among different network nodes, a Bayesian model is put forward for locating and tracing a network attack.

33. Wish you can benefit from our online sentence dictionary and make progress every day!

34. Bayesian more of mouthwash will help to keep the mouth clean.

35. A dual isomorphic Bayesian network model for medium voltage distribution system reliability re - assessment is also proposed.

36. The foundation of Bayesian decision theory is how to represent our values and beliefs.

37. The corresponding nonlinear threshold functions (bivariate shrinkage function) are derived from the model using the Bayesian estimation theory.

38. The paper introduces the target tracking algorithms based on Bayesian inference, which can be applied in the systems of nonlinearity and non-Gaussianity.

39. Bayesian network and Boolean network are powerful tools to genetic networks research.

40. Secondly, this thesis discusses the method of applying Bayesian Network inferring mechanism to educational hypermedia system.

41. The Bayesian estimation is derived through statistical analysis and it is shown to be equivalent to the maximization of the a Posteriori Probability.

42. Both likelihood ratio tests and Bayesian inference are employed to study the phylogeny of Phasianidae.

43. Two Bayesian network and Markov network structure learning methods are presented.

44. An image denoising method is proposed based on dual tree complex wavelet transform and Bayesian estimation.

45. The model can predict and decide to overcome the shortcomings of Bayesian reliability growth models.

46. An assessment technique that assesses vehicle dynamic performance using the data of rail measurement was developed by Bayesian estimation principle.

47. On the backdrop of electronic reconnaissance and infrared photographic reconnaissance, we develop a multisensor target identification system based on Bayesian Networks.

48. Beginning with the analysis of the Uncertainty in hypermedia system, the paper introduces the Bayesian networks.

49. Bayesian decision theory as part of the modern inductive logic has had a great influence logic.

50. We use Bayesian maximum a posteriori estimation training a speaker model from background model, to solve the problem of model miss matching in speaker verification system.

51. Bayesian estimation of parameters and index of reliability from two-parameter exponential distribution under time curtailed test were given.

52. Bayesian inference treats model parameters as random variables whereas frequentist inference considers them to be estimates of fixed, 'true' quantities.

53. Simultaneousty, the parameters, hyper parameters and model parameters at the other levels keep unchanged to simplify the parameters estimation of Bayesian feed forward networks.

54. RESULTS: This method can be used as variance analysis and data processing of Bayesian statistics evalustion.

55. Furthermore, prior probability of each knowledge point is determined by the directed acyclic graph based on knowledge points, and Bayesian Network based on knowledge points is built.

56. The results shows that the Bayesian Belief Network has better performance than the Decision Tree and Support Vector Machine.

57. Influence Diagrams(IDs) are graphical knowledge representation of decision problems and can be viewed as an extension of Bayesian Networks(BNs) with additional node types for decision and utility.

58. For example, we construct GPS and PPSP for phosphorylation site prediction, based on GPS and Bayesian Decision Theory algorithms, respectively.

59. The effect of informational external representation on Bayesian reasoning was studied from the perspective of distributed cognition.

60. Particle filter is a new real time inference algorithm, which is based on Bayesian inference and Monte Carlo method.