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A financial index forecasting model based on modified RBF neural network is proposed to find important points of stock index which can solve market identification problem. K-means algorithm is used to search initial center parameters of neurons and adjust optimal structure of network. And gradient descent method is set to search optimal centers through intelligent learning the operating mode of stock...
Lots of researchers have been studying on how to construct radial basis function neural networks. To determine the number and location of hidden neurons, a recursive procedure is adopted with a new evaluation criterion based on localized generalization error model (L-GEM). We derive a new sensitivity expression for Gaussian radial basis function neural network based on L-GEM, and get a new localized...
An integral part of China's economic reforms is the privatization of state-owned enterprises (SOEs) and listing the profitable units of the SOEs on the stock market. The two stock exchanges in Shanghai and Shenzhen were opened nearly twenty years ago. The Shenzhen stock exchange market is young and energetic. Moreover, it practices a T+1 settlement rule instead of real time trade as in Hong Kong or...
In order to improve the supplier selection and matching supply with demand for third party logistics integrated platform, this paper proposes a three-layer evaluation index system for supply and demand matching considering factors of service areas and cooperation experiences, establishes a supply and demand matching model based on neural network. This model perfectly simulates the process of fuzzy...
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