Titlebook: Advances in Neural Network Research and Applications; Zhigang Zeng,Jun Wang Book 2010 Springer Berlin Heidelberg 2010 Transport.cognition.

MEAN

REP

cliche

André Pereira,Manuel Correia,Pedro Brand?otrophe theory to determine whether the rock burst. And then the experimental data recorded are used for examining the model. The results show that the degree of prediction accuracy is high, and it proves that the prediction model of rock burst is feasible.

痛苦一下

關(guān)節(jié)炎

Bart Decker,Jorn Lapon,Andreas Uhl island intensity in Chuxiong city in 2006 with backpropagation neural network. The predicted value was 2.1815°C. Compared with its measured value, residual error was 0.1042, relative error was 4.5588model and GM(1,1) model. The result shows that backpropagation neural network is effective to predic

antiandrogen

Communications and Multimedia Securityvelet transform to decompose the original series into some filtered series, and a relevance vector machine whose kernel functions is wavelet function models each of them. Then, this method is used to predict fouling thermal resistance of Heat exchanger. Construction of wavelet relevance vector machi

輕浮思想

Lecture Notes in Computer Sciencehe acquired data series are non-linear and non-Gaussian. In this paper, Multi Layer Perceptrons (MLP) trained with minimizing error entropy (MEE) algorithm is utilized to forecast electricity price. Compared with the conventional MLP with mean square error (MSE) criterion, the proposed approach can

ordain

先行

Communications and Multimedia Security IIula, t Copula and Clayton Copula were used to describe the structure and extend the analysis from bivariate to any n-dimension. We apply this methodology to study the returns of a portfolio of four major foreign currencies in China. Our results suggest that the optimal investment allocations are sim

AGGER

A Modified Chaotic Cryptographic Methody and robust noise resistance. Thus, CMAC NNs are conventionally used in robot control. To solve financial time series forecasting, this paper presents an efficient CMAC NN scheme. The proposed CMAC NN transforms continuous values of input variables to discrete indexes by using a quantization operat