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The basic principle of combination forecasting is to give the proper weight combination into a single composite model from the results of each single forecasting model. Therefore, in the process of combination, each single model's advantages strengthened, and disadvantages weaken. Combination forecasting model has higher accuracy and reliability by integrating useful information of each single model...
This paper presents a novel approach for designing adaptive controller of nonlinear dynamical systems based on an improved quasi-ARX neural network prediction model. The improved quasi-ARX neural network prediction model has two parts: the linear part is used for stability and the nonlinear part is used to satisfy accuracy requirement. Then, we can obtain a linear controller and a nonlinear controller...
This paper studies learning transfer based on the adaptive learning theory, intelligence cognitive model theory and knowledge input theory under the large framework of updated cognitive theory of psychology. It mainly focuses on the method and experiment of positive transfer in production system self-adaptability model with the help of updated Artificial Neural Networks communication technology. These...
When a linear model is used for controlling nonlinear systems solely, it can't satisfy accuracy requirement. Whereas, although a neural network can deal with the accuracy problem, it may lead to instability. In this paper, an adaptive controller is proposed for nonlinear dynamical systems based on linear model and quasi-ARX neural network model. A switching algorithm is designed between the linear...
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