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Aiming at time-varying and complex nonlinear characteristics in the wood drying process, a double hidden process neural network was introduced into wood drying modeling. Time-varying and complex nonlinear characteristics of wood drying were considered adequately in wood drying model by time series data of main influence factors fitted to time-varying functions as network input. The concrete modeling...
For the multivariate forecast of Gross Domestic Product (GDP), the common features of traditional forecast methods are difficult to express the time cumulative effects in real forecast, and on the other hand, the factors influencing GDP have very typical timing characteristics. Therefore, in consideration of increasing GDP forecast accuracy, process neural network (PNN) was used into the GDP forecast...
Genetic process neural network (GPNN) is presented in this paper, after genetic algorithm was introduced into process neural networks. The concrete realization process and learning algorithm are given, and apply it into the prediction of economic time series. Making use of the characteristics of process neural network with time-varied input function, the prediction of economic time series is achieved,...
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