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Acute hypotension episodes are one of the hemodynamic instabilities with high mortality rate that is frequent among many groups of patients. Prediction of acute hypotension episodes can help clinicians to diagnose the cause of this physiological disorder and select proper treatment based on this diagnosis. In this study new physiological time series are generated based on heart rate, systolic blood...
The forecasting for total power of woodworking machinery is a complicated non-linear system, whose developmental changes have dual trends of increase and fluctuation. In the study, support vector machine trained by genetic algorithm is proposed to forecast the total power of woodworking machinery. Genetic algorithm is used to determine training parameters of support vector machine in this model, which...
This paper applied a genetic algorithm (GA) to optimize the parameters of support vector machine (SVM) for daily flow forecasting of Chickasaw creek located in Mobile County. To investigate the impact of variable enabling/disabling of flow, rainfall and evaporation on model prediction accuracy, four model structures with different input vectors were developed and the performance of them was evaluated...
Recent outbreak of corporate financial crises worldwide has brought attention to the need for a new international financial architecture which rests on crisis prediction and crisis management. Financial data have been widely used by researchers to predict financial crisis, but few studies exploit the use of non-financial indicators in corporate governance to construct financial crisis prediction model...
In the analysis of predicting financial distress based on support vector machine (SVM), the two parameters of SVM, c and sigma, which its value have important effect on the predicting accuracy, must be predetermined carefully. In order to solve this problem, this paper proposed a new culture genetic algorithm (CGA) to optimize the parameters of SVM. Through embedding GA into the cultural algorithm...
Support vector machine (SVM) has been applied to load forecasting field widely. However, if the training data has much noise and redundancy, the generalized performance of SVM will be weakened, so this can cause some disadvantages of slow convergence speed and low forecasting accuracy. A SVM forecasting model based on immune genetic fuzzy clustering algorithm (IGA-SVM) is presented, using immune genetic...
In the analysis of predicting financial distress based on support vector machine (SVM), irrelevant or correlated features in the samples could spoil the performance of the SVM classifier, leading to decrease of prediction accuracy. On the other hand, the improper determining of two SVM parameters will cause either over-fitting or under-fitting of a SVM model. In order to solve the problems mentioned...
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