Search results for "algoritmi"

Multiobjective muffler shape optimization with hybrid acoustics modelling

2010

Shape optimization of a duct system with respect to sound transmission loss is considered. The objective of optimization is to maximize the sound transmission loss at multiple frequency ranges simultaneously by adjusting the shape of a reactive muffler component. The noise reduction problem is formulated as a multiobjective optimization problem. The sound attenuation for each considered frequency is determined by a hybrid method, which requires solving Helmholtz equation numerically by finite element method. The optimization is performed using non-dominated sorting genetic algorithm, NSGA-II, which is a multi-objective genetic algorithm. The hybrid numerical method is flexible with respect …

Äänenvaimentimien mallinnuspohjainen monitavotteinen muodonoptimointi

2011

Multiobjective muffler shape optimization with hybrid acoustics modelling

2011

This paper considers the combined use of a hybrid numerical method for the modeling of acoustic mufflers and a genetic algorithm for multiobjective optimization. The hybrid numerical method provides accurate modeling of sound propagation in uniform waveguides with non-uniform obstructions. It is based on coupling a wave based modal solution in the uniform sections of the waveguide to a finite element solution in the non-uniform component. Finite element method provides flexible modeling of complicated geometries, varying material parameters, and boundary conditions, while the wave based solution leads to accurate treatment of non-reflecting boundaries and straightforward computation of the …

Serendipity in recommender systems

2018

The number of goods and services (such as accommodation or music streaming) offered by e-commerce websites does not allow users to examine all the available options in a reasonable amount of time. Recommender systems are auxiliary systems designed to help users find interesting goods or services (items) on a website when the number of available items is overwhelming. Traditionally, recommender systems have been optimized for accuracy, which indicates how often a user consumed the items recommended by system. To increase accuracy, recommender systems often suggest items that are popular and suitably similar to items these users have consumed in the past. As a result, users often lose interest…

Memory-saving optimization algorithms for systems with limited hardware

2011

Fāzes kodēšana aberāciju mērījumos

2022

Darbs ir uzrakstīts latviešu valodā uz 25 lapaspusēm. Tas satur 17 attēlus, 3 pielikumus un 40 atsauces uz literatūras avotiem. Darba mērķis: Novērtēt fāzes modulāciju intervāla ietekmi uz aberāciju mērīšanas kvalitāti. Metode: Dažāda apjoma simulētu un reālu aberāciju objektu imaginārās daļas, reālās daļas un viļņu frontes rekonstruēšana MATLAB, izmantojot dažāda modulāciju intervāla fāzes maskas un algoritmu PhaseLift. Rezultāti: Tika veiksmīgi rekonstruētas gan simulētu, gan reālu aberāciju objektu reālā (amplitūda) un imaginārā (fāze) daļa, un viļņu fronte, izmantojot PhaseLift algoritmu. Tika pārbaudīta PhaseLift algoritma efektivitāte pie dažāda apjoma aberācijām. Secinājumi: Mērāmo a…

On data mining applications in mobile networking and network security

2014

Taming big knowledge evolution

2016

Information and its derived knowledge are not static. Instead, information is changing over time and our understanding of it evolves with our ability and willingness to consume the information. When compared to humans, current computer systems seem very limited in their ability to really understand the meaning of things. On the other hand, they are very powerful when it comes down to performing exact computations. One aspect which sets humans apart from machines when trying to understand the world is that we will often make mistakes, forget information, or choose what to focus on. To put this in another perspective, it seems like humans can behave somehow more randomly and still outperform …

Automatic social distance estimation for photographic studies: Performance evaluation, test benchmark, and algorithm

2022

The social distancing regulations introduced to slow down the spread of COVID-19 virus directly affect a basic form of non-verbal communication, and there may be longer term impacts on human behavior and culture that remain to be analyzed in proxemics studies. To obtain quantitative results for such studies, large media and/or personal photo collections must be analyzed. Several social distance monitoring methods have been proposed for safety purposes, but they are not directly applicable to general photo collections with large variations in the imaging setup. In such studies, the interest shifts from safety to analyzing subtle differences in social distances. Currently, there is no suitabl…

Optimization of Linearized Belief Propagation for Distributed Detection

2020

In this paper, we investigate distributed inference schemes, over binary-valued Markov random fields, which are realized by the belief propagation (BP) algorithm. We first show that a decision variable obtained by the BP algorithm in a network of distributed agents can be approximated by a linear fusion of all the local log-likelihood ratios. The proposed approach clarifies how the BP algorithm works, simplifies the statistical analysis of its behavior, and enables us to develop a performance optimization framework for the BP-based distributed inference systems. Next, we propose a blind learning-adaptation scheme to optimize the system performance when there is no information available a pr…