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Automobile sells system plays an important role in automobile sales area, through the whole produce and management. Some forecast models have had unilateralism in some side nowadays, such as ARMA model. For example, the data of non-linearity has some error by ARMA model. This paper, assembles curve -regression model, Time Series Decomposition Model and RBF neural networks according to the weight distribution...
Radial basis function neural networks have been successfully applied to time series prediction in literature. Frequently, methods to build and train these networks must be given the past periods or lags to be used in order to create patterns and forecast any time series. This paper introduces E-tsRBF, a meta-evolutionary algorithm that evolves both the neural networks and the set of lags needed to...
Financial time series prediction has long been one of popular research areas for monetary policy makers, market participants and researchers. Inspired from the principle of self-organizing map, the author propose a topological regressive distributed model, which inherits the topology reserving advantage of self-organizing map and the simplicity of the normal autoregressive model. Comparison studies...
The CNY exchange rates can be viewed as financial time series which are charactered by high uncertainty, nonlinearity and time-varying behavior. Predictions for exchange rates of GBP-CNY and USD-CNY were carried respectively by means of RBF neural network forecasters. The detailed designs for architectures of RBF neural network models, transfer functions of the hidden layer nodes, input vectors and...
The rapid recognition problem of chaos in traffic flow was studied by using rough set neural network. Based on analyzing the demand of intelligent transportation system and the problems of the exiting recognition methods of chaos in traffic flow, the intelligent recognition method of chaos was proposed. The principle and the structure of the system are briefly introduced. There are online recognition...
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