Swarm-based descriptor combination and its application for image classification

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Detecção de falhas em estruturas inteligentes usando otimização por nuvem de partículas: fundamentos e estudo de casos

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fundamentos de otimização por inteligência de enxames: uma visão geral

Este artigo apresenta uma breve revisão de alguns dos mais recentes métodos bioinspirados baseados no comportamento de populações para o desenvolvimento de técnicas de solução de problemas. As metaheurísticas tratadas aqui correspondem às estratégias de otimização por colônia de formigas, otimização por enxame de partículas, algoritmo shuffled frog-leaping, coleta de alimentos por bactérias e colônia de abelhas. Os princípios biológicos que motivaram o desenvolvimento de cada uma dessas estratégias, assim como seus respectivos algoritmos computacionais, são introduzidos. Duas aplicações diferentes foram conduzidas para exemplificar o desempenho de tais algoritmos. A finalidade é enfatizar perspectivas de aplicação destas abordagens em diferentes problemas da área de engenharia.

Binary Bat Algorithm for Feature Selection

Feature selection aims to find the most important information to save computational efforts and data storage. We formulated this task as a combinatorial optimization problem since the exponential growth of possible solutions makes an exhaustive search infeasible. In this work, we propose a new nature-inspired feature selection technique based on bats behavior, namely, binary bat algorithm The wrapper approach combines the power of exploration of the bats together with the speed of the optimum-path forest classifier to find a better data representation. Experiments in public datasets have shown that the proposed technique can indeed improve the effectiveness of the optimum-path forest and outperform some well-known swarm-based techniques. © 2013 Copyright © 2013 Elsevier Inc. All rights reserved.

A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest

Besides optimizing classifier predictive performance and addressing the curse of the dimensionality problem, feature selection techniques support a classification model as simple as possible. In this paper, we present a wrapper feature selection approach based on Bat Algorithm (BA) and Optimum-Path Forest (OPF), in which we model the problem of feature selection as an binary-based optimization technique, guided by BA using the OPF accuracy over a validating set as the fitness function to be maximized. Moreover, we present a methodology to better estimate the quality of the reduced feature set. Experiments conducted over six public datasets demonstrated that the proposed approach provides statistically significant more compact sets and, in some cases, it can indeed improve the classification effectiveness. © 2013 Elsevier Ltd. All rights reserved.

Swarm Control Designs applied to a Mechanical Oscillator

This paper presented the particle swarm optimization approach for nonlinear system identification and for reducing the oscillatory movement of the nonlinear systems to periodic orbits. We analyzes the non-linear dynamics in an oscillator mechanical and demonstrated that this model has a chaotic behavior. Chaos control problems consist of attempts to stabilize a chaotic system to an equilibrium point, a periodic orbit, or more general, about a given reference trajectory. This approaches is applied in analyzes the nonlinear dynamics in an oscillator mechanical. The simulation results show the identification by particle swarm optimization is very effective.

Classification of petroleum well drilling operations with a hybrid particle swarm/ant colony algorithm

This paper describes an investigation of the hybrid PSO/ACO algorithm to classify automatically the well drilling operation stages. The method feasibility is demonstrated by its application to real mud-logging dataset. The results are compared with bio-inspired methods, and rule induction and decision tree algorithms for data mining. © 2009 Springer Berlin Heidelberg.

Swarm control designs applied to a micro-electro-mechanical gyroscope system (MEMS)

This paper analyzes the non-linear dynamics of a MEMS Gyroscope system, modeled with a proof mass constrained to move in a plane with two resonant modes, which are nominally orthogonal. The two modes are ideally coupled only by the rotation of the gyro about the plane's normal vector. We demonstrated that this model has an unstable behavior. Control problems consist of attempts to stabilize a system to an equilibrium point, a periodic orbit, or more general, about a given reference trajectory. We also developed a particle swarm optimization technique for reducing the oscillatory movement of the nonlinear system to a periodic orbit. © 2010 Springer-Verlag.

Projections Onto Convex Sets through Particle Swarm Optimization and its application for remote sensing image restoration

Image restoration attempts to enhance images corrupted by noise and blurring effects. Iterative approaches can better control the restoration algorithm in order to find a compromise of restoring high details in smoothed regions without increasing the noise. Techniques based on Projections Onto Convex Sets (POCS) have been extensively used in the context of image restoration by projecting the solution onto hyperspaces until some convergence criteria be reached. It is expected that an enhanced image can be obtained at the final of an unknown number of projections. The number of convex sets and its combinations allow designing several image restoration algorithms based on POCS. Here, we address two convex sets: Row-Action Projections (RAP) and Limited Amplitude (LA). Although RAP and LA have already been used in image restoration domain, the former has a relaxation parameter (A) that strongly depends on the characteristics of the image that will be restored, i.e., wrong values of A can lead to poorly restoration results. In this paper, we proposed a hybrid Particle Swarm Optimization (PS0)-POCS image restoration algorithm, in which the A value is obtained by PSO to be further used to restore images by POCS approach. Results showed that the proposed PSO-based restoration algorithm outperformed the widely used Wiener and Richardson-Lucy image restoration algorithms. (C) 2010 Elsevier B.V. All rights reserved.

Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Foraging Behavior of the Swarm-Founding Wasp, Polybia (Trichothorax) sericea (Hymenoptera, Vespidae): Prey Capture and Load Capacity

The main component of the protein diet of P. sericea was larvae of Lepidoptera (75.38%), with predominance of the following Families: Noctuidae (30.99%), Hesperiidae (19.01%); Pyralidae (19.01%) and Nymphalidae (11.98%). The average weight of the prey captured was 14.2 mg, a value equivalent to 24.7% of the average wasp weight. The average glucidic food load was 28.61 mg, corresponding to approximately half the wasp weight (49.64%). The weight of the load transported in the crop varied according to the food density, which, in turn, influenced the time spent in its collection (Pearson: n=64; r=0.64;p<0.05). Polybia sericea showed predatory interactions against Lepidopteran caterpillars, who are known to be agricultural pests. P. sericea has potential to be used in Integrated Pest Management.

Foraging Behavior of the Swarm-founding Wasp Polybia (Trichothorax) sericea (Hymenoptera, Vespidae): Daily Resource Collection Activity and Flight Capacity

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Morphological caste differences in the neotropical swarm-founding polistine wasp, Brachygastra lecheguana (Hymenoptera : Vespidae, Polistinae, Epiponini)

Morphological caste differences and ovary conditions were analyzed in colony of Brachygastra lecheguana. The results indicate the presence of individuals with ovary development but uninseminated (intermediates). In addition, these females were similar in morphology to workers, suggesting that, in this case, intermediates are ovary-developed workers. Queens were morphologically larger than workers and intermediates in some characters and smaller in others. Multivariate analysis showed that queens were highly distinct. These results indicate that castes are pre-imaginally determined in B. lecheguana.

Overview of Caste Differentiation in the Polistinae, Emphasizing the Neotropical Swarm-Founding Polistinae (Hymenoptera, Vespidae, Epiponini)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Caste Asymmetries in the Neotropical Swarm-Founding Wasp Polybia (Trychothorax) ignobilis (Hymenoptera, Vespidae, Epiponini)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)