Sentence examples for minimize a nonlinear from inspiring English sources

In such problems the amount of water to be released from each reservoir is chosen to minimize a nonlinear cost (or maximize benefit) function while satisfying proper constraints.

The equality of polynomial matrix and dft matrix decomposed matrices decompositions are guaranteed via the finite duration constraint, which is investigated in Section 4. The finite duration constraint imposes the phase angles of singular vector (eigenvector) to minimize a nonlinear quadratic function.

The computational mesh is automatically aligned to the implicitly described geometry by minimizing a nonlinear, constrained functional.

This reduces the alignment problem to minimizing a nonlinear sum-squared error function in order to best reconcile the observed images with the generative model.

This paper considers the problem of minimizing a nonlinear objective function subject to a system of bipolar fuzzy relational equations with max-(T_{L}) composition, where (T_{L}) is the Łukasiewicz triangular norm.

In this paper, we aim to tackle the problem of minimizing a nonlinear objective function subject to a system of bipolar max-(T_{L}) equations, i.e., left { textstylebegin{array}l@ min Z = f(mathbf{x}) mbox{subject to:} quad A^circmathbf{x} vee A^circnegmathbf{x} = mathbf{b}.

The system coefficients c 1 c 9 and d 0 d 9 are computed through minimizing a nonlinear least-squares error function as, arg mathop {hbox{min} }limits_{c,d} mathop sum limits_{k = 1}^{m} left( {frac{{f_{c} }}{{f_{d} }} - z_{k}^{b} } right)^{2}, (23 where k is the ordinal number of each point and m denotes the total number of points.

The problem of minimizing a general nonlinear objective function subject to a system of max-T equations has been tackled by Lu and Fang [17], Khorram and Hassanzadeh [18], and Hassanzadeh et al. [19] using the genetic algorithm.

In the Rietveld method, the weighted sum of squares residual, S r, between the observed and the calculated intensities of powder diffraction data is minimized in a nonlinear least-squares method.

The outcome of our investigation is a recommendation for the use of nonlinear optimization techniques that minimize a fairness functional based on the variation of curvature.

To obtain optimal parameter estimates (by minimizing a cost function) of nonlinear models and measurements data with statistical uncertainty descriptions, methods using global or local optimization can be considered [e.g. Moles et al. (2003)].