Empirical studies have shown that decision makers do not usually treat probabilities linearly. Instead, people tend to overweight small probabilities and underweight large probabilities. One way to model such distortions in decision making under risk is through a probability weighting function. We present a nonparametric estimation procedure for assessing the probability weighting function and ...

Acquisition-weighting improves the localization of MRI experiments. An approach to acquisition-weighting in a purely phase-encoded experiment is presented that is based on a variation of the sampling density in k-space. In contrast to conventional imaging or to accumulation-weighting, where k-space is sampled with uniform increments, density-weighting varies the distance between neighboring sam...

Many of the conventional similarity methods assume that molecular fragments that do not relate to biological activity carry the same weight as the important ones. One possible approach to this problem is to use the Bayesian inference network (BIN), which models molecules and reference structures as probabilistic inference networks. The relationships between molecules and reference structures in...

in this paper the inversion of gravity data using l1–norm stabilizer is considered. the inversion is an important step in the interpretation of data. in gravity data inversion, the goal is to estimate density and geometry of the unknown subsurface model from a set of known observation measured on the surface. commonly, rectangular prisms are used to model the subsurface under the survey area. t...

In this paper, we propose a method how to construct density weighting functions from Copulas. The notion of Copula was introduced by A. Sklar in 1959. A Copula is a dependence function to construct a bivariate distribution function that links joint distributions to their marginals. Other forms of dependence function, based on density weighing functions, have also been developed. The proposed me...

In this study, the performance of the algorithms of whale, Differential evolutionary, crow search, and Gray Wolf optimization were evaluated to operate the Golestan Dam reservoir with the objective function of meeting downstream water needs. Also, after defining the objective function and its constraints, the convergence degree of the algorithms was compared with each other and with the absolut...

This paper presents a solution method for fixed multichannel frequency domain feedforward controller, which is optimized different sound field disturbances, each corresponding to control objective. A controller determined on the basis of identical objectives disturbances can be solved efficiently by using inverse two relatively small matrices, Hermitian square secondary path and cross-spectral ...

In recent years, scheduling optimization has been utilized in production systems. To construct a suitable mathematical model of problem, modeling techniques that can automatically select an appropriate objective function from historical data are necessary. This paper presents two methods to estimate weighting factors the problem data, given information operation time and setup costs. We propose...

<span>This article proposes a new metaheuristic algorithm called Archimedes optimization (AOA) for solving problems of optimal power flow (OPF) utilizing the renewable energy sources (RES) minimizing different single-objective and multi-objective functions based on minimization fuel cost, losses transmission lines, emission voltage profile improvement. Also, mathematical formulation is in...

In the present work, optimal balancing of planar six-bar mechanism is investigated to minimize fluctuations shaking force and moment. An optimization problem formulated for by developing an objective function. The genetic algorithm MINITAB software were used solve problem. selection weighting factors has a crucial role obtain optimum values design parameters. Two sets considered as per contribu...