In the present paper, we propose an approach of combination prediction of chaotic time series. The method is based on the adding-weight one-rank local-region method of chaotic time series. The method allows us to define an interval containing a future value with a given probability, which is obtained by studying the prediction error distribution. Its effectiveness is shown with data generated by Logistic map.
In the present paper, the fractal rough surface is described by a band-limited Weierstrass-Mandelbrot function. By using the Monte Carlo method and optimal method, a minimal target function method is applied to inverting the fractal dimension of the fractal rough surface. Numerical simulations show that the method can avoid the influence of the fractal characteristic scale, and that the method is of high precision.
