Search results for "A* algorithm"

3D inter-subject medical image registration by scatter search

2005

Image registration is a very active research area in computer vision, namely it is used to find a transformation between two images taken under different conditions. Point matching is an image registration approach based on searching for the right pairing of points between the two images. From this matching, the registration transformation we are searching, can be inferred by means of numerical methods. In this paper, we propose a scatter search (SS) algorithm to solve the matching problem. SS is a hybrid metaheuristic with a good trade-off between search space diversification and intensification. On the one hand, diversity is basically introduced from a population-based approach where syst…

Context-dependent foraging habitat selection in a farmland raptor along an agricultural intensification gradient

2021

Abstract Gradients of agricultural intensification in agroecosystems may determine uneven resource availability for predators relying on these man-made habitats. In turn, these variations in resource availability may affect predators’ habitat selection patterns, resulting in context-dependent habitat selection. We assessed the effects of gradients of landscape composition and configuration on habitat selection of a colonial farmland bird of prey, the lesser kestrel (Falco naumanni), relying on 76 GPS-tracked nestling-rearing individuals from 10 populations scattered along an agricultural intensification gradient. Analyses were conducted considering two ecological levels of aggregation (the …

On the computational aspects of a symmetric multidomain BEM for elastoplastic analysis

2012

The symmetric boundary element method (SBEM) is applied to the elasto-plastic analysis of bodies subdivided into substructures. This methodology is based on the use of: a multidomain SBEMapproach, for the evaluation of the elastic predictor; a return mapping algorithm based on the extremal paths theory, for the evaluation of inelastic quantities characterizing the plastic behaviour of each substructure; and a transformation of the domain inelastic integrals of each substructure into corresponding boundary integrals. The elastic analysis is performed by using the SBEM displacement approach, which has the advantage of creating system equations that only consist of nodal kinematical unknowns a…

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 …

The Bayesian Pursuit Algorithm: A New Family of Estimator Learning Automata

2011

Published version of a chapter in the book: Modern Approaches in Applied Intelligence. Also available from the publisher at http://dx.doi.org/10.1007/978-3-642-21827-9_53 The fastest Learning Automata (LA) algorithms currently available come from the family of estimator algorithms. The Pursuit algorithm (PST), a pioneering scheme in the estimator family, obtains its superior learning speed by using Maximum Likelihood (ML) estimates to pursue the action currently perceived as being optimal. Recently, a Bayesian LA (BLA) was introduced, and empirical results that demonstrated its advantages over established top performers, including the PST scheme, were reported. The BLA scheme is inherently …

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

Optimization of Delayed-State Kalman-Filter-based Algorithm via Differential Evolution for Sensorless Control of Induction Motors

2010

This paper proposes the employment of the differential evolution (DE) to offline optimize the covariance matrices of a new reduced delayed-state Kalman-filter (DSKF)-based algorithm which estimates the stator-flux linkage components, in the stationary reference frame, to realize sensorless control of induction motors (IMs). The DSKF-based algorithm uses the derivatives of the stator-flux components as mathematical model and the stator-voltage equations as observation model so that only a vector of four variables has to be offline optimized. Numerical results, carried out using a low-speed training test, show that the proposed DE-based approach is very promising and clearly outperforms a cla…