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This paper proposes a method to give an early warning of an abrupt change of price in a foreign exchange market. Volatility is a quantification of how much a value moves in a time series. It is now customary to assume that volatility of foreign exchange markets is time-varying. Intuitively we observe that there are at least two states or regimes: one is with low volatility and the other is with high...
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...
Innovation system efficiency analysis and prediction play an important role in regional innovation systems development and improve benefit of innovative capacity for country. According to the county innovation system data which is large scale and imbalance, this paper presented a support vector machine model to predict county innovation system efficiency. The method was compared with artificial neural...
Using support vector machine (SVM) with a time-dependent structure, a new model is proposed to predict short-time traffic flow volume. In order to match the time varying characteristic of the traffic flow volume, in the developed model, each prediction requires a reconstruction process of SVM structure. The current SVM structure is determined by restraining with the input of the data of the traffic...
Spontaneous Combustion in Coal Seam (SCCS) is seriously threatening coal mine safety. A novel approach to predict SCCS by using Support Vector Machine (SVM) is present. The SVM is based on statistical learing theory with a simple structure and good generation properties. The basic SVM principle was firstly reviewed. Then, the kernel function was choiced, and the model parameters were optimized with...
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