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The prediction of fill levels in stormwater tanks is an important practical problem in water resource management. In this study state-of-the-art CI methods, i.e., Neural Networks (NN) and Genetic Programming (GP), are compared with respect to their applicability to this problem. The performance of both methods crucially depends on their parametrization. We compare different parameter tuning approaches,...
Two Computational Intelligence techniques, neural networks-based Multivariate Time Series Model Mining (MVTSMM) and Genetic Programming (GP), have been used to explore the possible relationship between solar activity and temperatures in Central England for the 1721 to 1967 period. Data driven analysis of multivariate, heterogeneous and incomplete time series are used in order to understand the extreme...
The self-similar and nonlinear nature of network traffic makes high accurate prediction difficult. Various technology, including Autoregressive Integrated Moving Average (ARIMA), Local Approximation (LA), Neural Network (NN) etc., have been applied to internet traffic prediction. In this paper, Complex Network based on genetic programming and particle swarm optimization is proposed to predict the...
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