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A new method to develop a parametric model based on genetic algorithm (GA) and support vector machines (SVM) is proposed. The proposed method is achieved in three steps. In the first step, the non-stationarity of the series is identified. If the time series is stationary, the second step is executed directly. If the time series has the characteristics of non-stationarity, the non-stationary time series...
A new method to develop a parametric model based on genetic algorithm (GA) and support vector machines (SVM) is proposed. The proposed method is achieved in three steps. In the first step, the non- stationarity of the series is identified. If the time series is stationary, the second step is executed directly. If the time series has the characteristics of non-stationarity, the non-stationary time...
A new time series prediction method based on support vector machines (SVMs) experts and genetic algorithm (GA) is proposed. The proposed method has a three-stage architecture. In the first stage, self-organizing feature map (SOM) is used as a clustering algorithm to partition the whole input space into several disjointed regions. Then, in the second stage, GA is adopted to determine the parameter...
A new method for the voidage measurement of gas-oil two-phase flow was proposed. The voidage measurement was implemented by the identification of flow pattern and a flow pattern specific voidage measurement model. The flow pattern identification was achieved by combining the fuzzy pattern recognition technique and the crude cross-sectional image reconstructed by the simple back projection algorithm...
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