Many studies on reducing greenhouse gas emissions from ships have been conducted to reduce environmental pollution. Reducing the fuel oil consumption of traditional and green is a key focus these studies. The ship depends electric loads. Thus, power load estimation necessary develop methods for ships. However, data accessibility low, limiting number relevant This study proposes model estimating...

We propose a semidefinite optimization (SDP) model for the class of minimax two-stage stochastic linear optimization problems with risk aversion. The distribution of second-stage random variables belongs to a set of multivariate distributions with known first and second moments. For the minimax stochastic problem with random objective, we provide a tight SDP formulation. The problem with random...

Representation of a given nonnegative multivariate polynomial in terms of a sum of squares of polynomials has become an essential subject in recent developments of a sum of squares optimization and SDP (semidefinite programming) relaxation of polynomial optimization problems. We disscuss effective methods to get a simpler representation of a “sparse” polynomial as a sum of squares of sparse pol...

Representation of a given nonnegative multivariate polynomial in terms of a sum of squares of polynomials has become an essential subject in recent developments of sums of squares optimization and SDP (semidefinite programming) relaxation of polynomial optimization problems. We disscuss effective methods to obtain a simpler representation of a “sparse” polynomial as a sum of squares of sparse p...

The paper is concerned with the multivariate global optimization with box constraints. A new underestimator is investigated for twice continuously differentiable function on a box which is an extension of the approach developed in [5] for univariate global optimization. AMS Subject Classification: 65K05, 90C30, 90C34

This is a survey of a recent methodology to solve systems of polynomial equations and inequalities for problems arising in combinatorial optimization. The techniques we discuss use the algebra of multivariate polynomials with coefficients over a field to create large-scale linear algebra or semidefinite programming relaxations of many kinds of feasibility or optimization questions.

in this paper, in order to optimize the portfolio consisting of selected industrial stocks of petroleum products, automobiles and parts, electrical industry and extraction of minerals from tehran stock exchange member, first, time – varying conditional covariance matrix has been estimated based on the following multivariate garch models: diagonal-vech (1,1), ccc (1,1) and diagonal -bekk (1,1). ...

We consider a problem of blind signal extraction from noisy multivariate data, in which each datum represents a system's response, observed under a particular experimental condition. Our prototype example is multipixel functional images of brain activity in response to a set of prescribed experimental stimuli. We present a novel multivariate analysis technique, which identifies the different ac...

The aim of the present work is that of analysing the data of snow-cover measurements carried out in the northeastern Alps by the Italian National Electricity Board (ENEL) since 1966, in order to select a reduced number of measurement stations from which to evaluate the water equivalent amount. The selection was based on cluster methods for identification of homogeneous areas and afterwards on p...

We discuss the optimization of the stochastic relaxation of a real-valued function, i.e., we introduce a new search space given by a statistical model and we optimize the expected value of the original function with respect to a distribution in the model. From the point of view of Information Geometry, statistical models are Riemannian manifolds of distributions endowed with the Fisher informat...