Although the RBF is the most widely used SVR kernel function,the expression complexity of RBF makes it difficult to get analytical formula of rolling optimization in model predictive control.A model of predictive control based on RBF-SVR is established,the multi-agent particle swarm optimization (...
To ensure the candidate points corresponding to the edges with a higher error indicator value have a better chance of being accepted, we introduce a formula that determines each edge’s adaptive separation on tolerance value based on its error indicator value. Furthermore, we prioritize the ...
Moreover, our proposed MPE formula outperforms other selection methods used for fault-free neural networks. 展开 关键词: faulty neural networks multi-node open fault radial basis function kernel width mean prediction error DOI: 10.1007/s11063-010-9145-x ...
Curve fittingNeural networksStopping powerThis article presents a new framework for fitting measured scientific data to a simple empirical formula by introducing an additional linear neuron to the standard Gaussian kernel radial basis function (RBF) neural networks. The proposed method is first used to...
Curve fittingNeural networksStopping powerThis article presents a new framework for fitting measured scientific data to a simple empirical formula by introducing an additional linear neuron to the standard Gaussian kernel radial basis function (RBF) neural networks. The proposed method is first used to...
Simulation results show that the chosen optimal kernel width by our proposed MPE formula is very close to the actual one by the conventional method. Moreover, our proposed MPE formula outperforms other selection methods used for fault-free neural networks....
The inverse model formula shared by both neural controllers is given below: 𝐹(𝑘)=RBF(𝑣(𝑘),𝜃(𝑘),𝜃˙(𝑘),𝜃(𝑘+1))F(k)=RBF(v(k),θ(k),θ˙(k),θ(k+1)) (26) Table 4. Notation and parameter values for the inverted pendulum. The state Equations (25...
Formula (15), which estimates the first derivative of a suitably differentiable function 𝑢(𝑥)u(x) evaluated at the nodes given by (14), demonstrates the 2nd speed of convergence. Proof. To verify this convergence speed, we must use the weights derived analytically in Equations (19)–...
A closed-form formula for the RBF-based approximation of the Laplace-Beltrami operator. J. Sci. Comput. 2018, 77, 1115–1132. [Google Scholar] [CrossRef] [Green Version] ÁLvarez, D.; González-Rodríguez, P.; Kindelan, M. A local radial basis function method for the Laplace-Beltrami...
G repetitions of the formula yield the chaotic sequence, after which the scale is converted and the P and G of each particle are updated. Step 5: Determine whether the maximum number of iterations of chaos has been reached; if not, return to step 3. 2.5. CPSO-RBF-BP Reactor Temperature...