Applications of computer simulation in statistical optimization problems

2011 ◽  
Author(s):  
Yong Zhou
Keyword(s):  
Computer Simulation ◽  
Optimization Problems ◽  
Statistical Optimization

scholarly journals Mathematical relations for constructing an algorithm for estimating signal parameters under conditions of constraints

2021 ◽  
pp. 153-156
Author(s):  
Я.Я. Эглит ◽  
К.Я. Эглите ◽  
А.А. Ковтун ◽  
Д.А. Глушко
Keyword(s):  
Transport System ◽  
Optimization Problems ◽  
Inequality Constraint ◽  
Statistical Optimization ◽  
Computing Environment ◽  
Dummy Variables ◽  
Signal Parameters ◽  
Main Production ◽  
Mathematical Relationships ◽  
Mathematical Relations

Статья посвящена разработке математических соотношений для построения алгоритма оценивания параметров сигналов в условиях ограничений. При работе транспортной системы возникают довольно сложные проблемы, которые связаны с необходимостью проведения оценки принятых параметров с требованиями соблюдения имеющихся ограничений. Ограничения могут представлять собой как равенства, так и неравенства. Поскольку ограничения-неравенства могут быть сведены путём добавления фиктивных переменных к условиям, а также их можно проверить по шагам, переводя в состав равенства, в статье разработан алгоритм, позволяющий иметь ограничения-равенства. Данная задача относится к классу статистических проблем оптимизации. Для ее решения использованы стандартные функции из подкаталога "optimization" вычислительной среды MatLAB. Построение такого алгоритма даст возможность не только уменьшить складские расходы, но и сократить основное производственное время. The article is devoted to the development of mathematical relationships for constructing an algorithm for estimating signal parameters under constraints. During the operation of the transport system, rather complex problems arise, which are associated with the need to assess the adopted parameters with the requirements of compliance with the existing restrictions. Constraints can be either equality or inequality. Since the inequality constraint can be reduced by adding dummy variables to the equality conditions, and they can also be checked step by step, transforming them into equality, we will develop an algorithm that allows us to have equality constraints. This task belongs to the class of statistical optimization problems. To solve it, standard functions from the "optimization" subdirectory of the MatLAB computing environment will be used. The construction of such an algorithm will make it possible not only to reduce storage costs, but also to reduce the main production time.

scholarly journals Some Notes on Concordance between Optimization and Statistics

2019 ◽  
Vol 2019 ◽  
pp. 1-6
Author(s):  
Weiyan Mu ◽  
Qiuyue Wei ◽  
Shifeng Xiong
Keyword(s):  
Maximum Likelihood ◽  
General Framework ◽  
Optimization Problem ◽  
Theoretical Study ◽  
Optimization Problems ◽  
Likelihood Estimation ◽  
Statistical Optimization ◽  
Comparison Theorems ◽  
Engineering Problems ◽  
Statistical Sense

Many engineering problems require solutions to statistical optimization problems. When the global solution is hard to attain, engineers or statisticians always use the better solution because we intuitively believe a principle, called better solution principle (BSP) in this paper, that a better solution to a statistical optimization problem also has better statistical properties of interest. This principle displays some concordance between optimization and statistics and is expected to widely hold. Since theoretical study on BSP seems to be neglected by statisticians, this paper presents a primary discussion on BSP within a relatively general framework. We demonstrate two comparison theorems as the key results of this paper. Their applications to maximum likelihood estimation are presented. It can be seen that BSP for this problem holds under reasonable conditions; i.e., an estimator with greater likelihood is better in some statistical sense.

Characterization of Modulated Structure Through Structure Images and their Computer Simulation

1990 ◽  
Vol 48 (1) ◽  
pp. 70-71
Author(s):  
Kiyomichi Nakai ◽  
Yusuke Isobe ◽  
Chiken Kinoshita ◽  
Kazutoshi Shinohara
Keyword(s):  
Computer Simulation ◽  
High Resolution ◽  
Spherical Aberration ◽  
High Resolution Electron Microscopy ◽  
Basic Mechanism ◽  
Objective Lens ◽  
Specimen Thickness ◽  
Transmitted Beam ◽  
Modulated Structure ◽  
Resolution Electron

Induced spinodal decomposition under electron irradiation in a Ni-Au alloy has been investigated with respect to its basic mechanism and confirmed to be caused by the relaxation of coherent strain associated with modulated structure. Modulation of white-dots on structure images of modulated structure due to high-resolution electron microscopy is reduced with irradiation. In this paper the atom arrangement of the modulated structure is confirmed with computer simulation on the structure images, and the relaxation of the coherent strain is concluded to be due to the reduction of phase-modulation.Structure images of three-dimensional modulated structure along <100> were taken with the JEM-4000EX high-resolution electron microscope at the HVEM Laboratory, Kyushu University. The transmitted beam and four 200 reflections with their satellites from the modulated structure in an fee Ni-30.0at%Au alloy under illumination of 400keV electrons were used for the structure images under a condition of the spherical aberration constant of the objective lens, Cs = 1mm, the divergence of the beam, α = 3 × 10-4 rad, underfocus, Δf ≃ -50nm and specimen thickness, t ≃ 15nm. The CIHRTEM code was used for the simulation of the structure image.

Averting robo-bees: why free-flying robotic bees are a bad idea

2019 ◽  
Vol 3 (6) ◽  
pp. 723-729
Author(s):  
Roslyn Gleadow ◽  
Jim Hanan ◽  
Alan Dorin
Keyword(s):  
Climate Change ◽  
Computer Simulation ◽  
Food Security ◽  
European Countries ◽  
Plant Interactions ◽  
Plant Insect Interactions ◽  
Native Habitat ◽  
Insect Pollinators ◽  
Insect Interactions

Food security and the sustainability of native ecosystems depends on plant-insect interactions in countless ways. Recently reported rapid and immense declines in insect numbers due to climate change, the use of pesticides and herbicides, the introduction of agricultural monocultures, and the destruction of insect native habitat, are all potential contributors to this grave situation. Some researchers are working towards a future where natural insect pollinators might be replaced with free-flying robotic bees, an ecologically problematic proposal. We argue instead that creating environments that are friendly to bees and exploring the use of other species for pollination and bio-control, particularly in non-European countries, are more ecologically sound approaches. The computer simulation of insect-plant interactions is a far more measured application of technology that may assist in managing, or averting, ‘Insect Armageddon' from both practical and ethical viewpoints.

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