Quantitative and data mining approach has been created to enhance the emphasis of the clinical signal detection procedure. The process employed, is known as the BCPNN (Bayesian Confidence Propagation Neural Network). This not just aids in the early detection of adverse drug
In this study, numerous statistical models like multiple discriminant analysis, ordinal logit and probit regression analysis, cluster analysis, neural network analysis, and decision tree were used to predict the credit ratings of US financial corporations. It was discovered that principal components analysis
Nowadays, investors are more willing to make investment on exchange market to gain much more superior returns. There is an increasing demand on credit information of corporations. However, there are only a few of Hong Kong corporations have been evaluated by credit rating agencies.
This thesis concerns optimization of structures considering various uncertainties. The overall objective is to find methods to create solutions that are optimal both in the sense of handling the typical load case and minimising the variability of the response, i.e. robust optimal designs.Traditionally optimized structures may show a tendency of being sensitive to small perturbations in the design or loading conditions, which of course are inevitable.
In this work we compare the prediction performance of three optimized technical indicators with a Support Vector Machine Neural Network. For the indicator part we picked the common used indicators: Relative Strength Index, Moving AverageConvergence Divergence and Stochastic Oscillator. For the Support
Gaze tracking means to detect and follow the direction in which a person looks. This can be used in for instance human-computer interaction. Most existing systems illuminate the eye with IR-light, possibly damaging the eye. The motivation of this thesis is to