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When combining grey system with RBF neural network, local optimization and convergence problems are still existed, so genetic algorithm is introduced to assist the modeling of grey neural network in this paper. Firstly, genetic algorithm is employed to solve the parameters of improved GM(1,1) with Lagrange's value theorem, and then RBF neural network is parallel connected to compensate errors. A new...
A new prediction model that combining the merits of support vector machine (SVM) and gray RBF neutral network is proposed in this paper. First apply structural risk minimization principle to optimize the modeling method of RBF neutral network, so that the radial basis centers and network weights could be acquired directly. Then use error compensator of RBF neutral network based on structural risk...
A new prediction model of small sample for time-displacement data based on RBF and GM(0, N), called grey RBF (GRBF) prediction model, was proposed in this paper. RBF network has good ability in approaching nonlinear function, and its convergent speed is rapid, but its precision and stability strongly depended on sample capability. While GM(0, N) can make an accurate precision of small sample data,...
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