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Artificial neural networks (ANNs) have been applied to a variety of classification and learning tasks. The use of evolutionary algorithms (EA) as one of the fastest, robust and efficient global search techniques has allowed different properties of artificial neural networks to be evolved. This paper proposes the possibility of using differential evolution for determining an ANN architecture (DNNA)...
In this work, artificial neural networks (ANN) based on genetic algorithm (GA) have been developed to predict energy consumption in China. The numbers of neurons in the hidden layer, the momentum rate and the learning rate are determined using the genetic algorithm. The inputs to the artificial neural networks model are four variables, namely, gross domestic product, industrial structure, total population...
The stock market bubbles present different properties in different economic environments and stages, and their impacts on the economic system are varied. In this paper, self organizing map (SOM) and principal component analysis (PCA) were employed to determine the property of the stock bubbles in Shanghai stock market from Jan-2000 to Apr-2008. The nature of the bubbles was interpreted by factor analysis...
Investment risks assessment of high-tech projects is a more complex process, involving various factors and it is not entirely the linear relationship between influencing factors and measurement results. Artificial neural network (ANN) has a strong nonlinear mapping ability, with strong learning ability and high classification and prediction accuracy. The paper applied ANN to establish a new risk assessment...
The pricing method of new shares issuing based on artificial neural network is studied in this paper. A three-layer neural network model is established and simulation tests are carried out. It shows that the BP network model established fits well with the real first day's closing price of stock and greatly improves the IPO pricing. It provides a new way to investors for forecasting IPO price of small...
High-tech industry zone play a important role in the global economic system with the continuously new knowledge innovation, itpsilas becoming the main motion of regional economic structure optimization and competition. The technology ability and diffuse effect of High-tech zone influence itself and regional economic development greatly. This paper design High-tech zone technology innovation ability...
The classification and identification technology plays an important role in the research of brain-computer interface (BCI) systems. In this paper, we do fuzzy clustering disposal for the multi-channel electroencephalogram (EEG) during finger movement at first according to event-related desynchronization phenomena (ERD) in the event-related EEG. Then we classify signal-trial EEG with the feature extracted...
Target selection is one of the most important steps of during the process of mergers and acquisitions. Hopfield neural network is very strong in pattern recognition which can simulate the criteria of acquirer and remind it. The network model overcomes the shortcomings of classic statistic and fuzzy models and embodies the requirements of acquirer. Demonstration shows that Hopfield network is an effective...
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...
Aimed at the engine rotor fault, a new diagnosis method based on Wavelet Transform and artificial neural network (ANN) is proposed. Firstly, according to the wavelet transform theories, the original signals are sampling repeatedly, and the continuous wavelet transform (CWT) is used for the signals sampled. Afterward, the obtained signals are decomposed to fixed layer so as to obtain the frequency...
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