This paper addresses a new spectral collocation method for solving nonlinear fractional quadratic integral equations. The main idea of this method is to construct the approximate solution based on fractional order Chelyshkov polynomials (FCHPs). To this end, first, we introduce these polynomials and...
Miura, H., Hashimoto, Y., and Takagi, T. Extended al- gorithm for solving underdefined multivariate quadratic equations. IEICE Transactions, 97-A(6):1418-1425, 2014.H. Miura, Y. Hashimoto, and T. Takagi. Extended algorithm for solving underdefined multivariate quadratic equations. In ...
Here we favor the original quadratic formulation, since we explicitly need the filling-in effect of a nonrobust regularizer to fill in the information in masked regions. To overcome the problem of having a nonconvex energy in (13.5), the coarse-to-fine warping scheme can be used as ...
According to the produced output active power, Eq. (5) describes the traditional OPF function in Ths as a quadratic objective function. Also, Eq. (6) contains the OPF model for Ths that includes VPEs, where \({r}_{i}\) and \({p}_{i}\) stand for the VPEs specifications while \...
Classically, in the worst-case scenario, f(x) has to be evaluated a total of N−1 times, where N=2n, trying out all the possibilities. After N−1 elements, it must be the last element. Grover's quantum algorithm can solve this problem much faster, providing a quadratic speed up....
the algorithm is applicable to both heat and Poisson’s equations comparing to their analytical solutions. The outline of this paper is as follows. In Sect.2, we supply auxiliary tools to solve linear matrix equations and to make a convergence analysis of an iterative method for solving such ...
In other vernacular, r is known as the “modular residue,” which leads to “quadratic residue”1 and other forms of residues. Modular reductions are normally used to create finite groups, rings, or fields. The most common usage for performance driven modular reductions is in modular ...
With the CEC'2020 test suite, the mAHA has been compared to several other meta-heuristics for addressing global optimization challenges. To test the algorithm's feasibility, standard and modified test systems were used to solve the OPF problem. To assess the effectiveness of mAHA, the results ...
Generally, applying the filtering algorithm on this basis involves modeling the state space by constructing state equations and characterizing the SOH as state variables using parameters, such as internal resistance and capacity, to dynamically track and predict the health condition and iteratively solve ...
This method, which we call NE/SQP (for Nonsmooth Equations/Successive Quadratic Programming), is a damped Gauss—Newton algorithm applied to solve a certain nonsmooth-equation formulation of the complementarity problem; it is intended to overcome a major deficiency of several previous methods of this...