Electricity price predictions have become a major discussion on competitive market under deregulated power system. But, the exclusive characteristics of electricity price such as non-linearity, non-stationary and time-varying volatility structure present several challenges for this task. In this paper, a new forecast strategy based on the iterative neural network is proposed for Day-ahead price...

This work presents the rst direct method for specii-cally tting ellipses in the least squares sense. Previous approaches used either generic conic tting or relied on iterative methods to recover elliptic solutions. The proposed method is (i) ellipse-speciic, (ii) directly solved by a generalised eigen-system, (iii) has a desirable low-eccentricity bias, and (iv) is robust to noise. We provide a...

A generalised multiquadric radial basis function is a function of the form s(x) = ∑N i=1 diφ(|x − ti|), where φ(r) = ( r2 + τ2 )k/2 , x ∈ Rn, and k ∈ Z is odd. The direct evaluation of an N centre generalised multiquadric radial basis function at m points requires O(mN) flops, which is prohibitive when m and N are large. Similar considerations apparently rule out fitting an interpolating N cent...

In geophysical applications direct current (DC) resistivity surveys are collected by injecting current and recording voltage potentials over a field site of interest. These data sets can provide valuable non-invasive images of the sub-surface. The optimization problem that arrises in producing these images requires multiple solves of a linear system with numerous right hand sides (RHSs). Due to...

Numerical simulations of acoustic scattering in the frequency domain based on hybrid methods coupling finite elements and boundary elements are the most suited for dealing with problems involving wave propagation in inhomogeneous media. Furthermore, it is necessary to resort to high performance computing to effectively solve the large size problems. However, the direct coupling yields a linear ...

Data assimilation is an essential tool for predicting the behavior of real physical systems given approximate simulation models and limited observations. For many complex systems, there may exist several models, each with different properties and predictive capabilities. It is desirable to incorporate multiple models into the assimilation procedure in order to obtain a more accurate prediction ...

We propose a new iterative method for the numerical computation of the solution of linear systems of equations. The method is suited to problems exhibiting local dependencies. The technique can be envisaged as a generalization of the Gauss-Seidel point iterative method, being able to achieve greater convergence rates with, approximately, the same number of operations per iteration. On each iter...

The aim of this work is to carry out a systematic experimental study of the use of iterative techniques in the context of solving the linear system of equations arising from the solution of the diffusion–convection equation with variable velocity field through the use of the dual reciprocity method in multidomains (DRMMD). We analyse the efficiency and accuracy of the computed solutions obtaine...

In this paper, we present a direct solution method based neural network for image compression. The proposed technique includes steps to break down large images into smaller windows and eliminate redundant information. Furthermore, the technique employs a neural network trained by a non-iterative, direct solution method. An error backpropagation algorithm is also used to train the neural network...