Artificial Immune Systems - Models, algorithms and applications

Copyright © 2010 Academic Research Publishing Agency.This article has been made available through the Brunel Open Access Publishing Fund.Artificial Immune Systems (AIS) are computational paradigms that belong to the computational intelligence family and are inspired by the biological immune system. During the past decade, they have attracted a lot of interest from researchers aiming to develop immune-based models and techniques to solve complex computational or engineering problems. This work presents a survey of existing AIS models and algorithms with a focus on the last five years.This article is available through the Brunel Open Access Publishing Fun

A comparison of different evolutive niching strategies for identifying a set of selfsimilar contractions for the IFS inverse problem

The key problem in fractal image compression is that of obtaining the IFS code (a set of linear transformations)which approximates a given image with a certain prescribed accuracy (inverse IFS problem).In this paper,we analyze and compare the performance of sharing and crowding niching techniques for identifying optimal selfsimilar transformations likely to represent a selfsimilar area within the image. The best results are found using the deterministic crowding method.We also present an nteractive Matlab program implementing the algorithms described in the paper.The key problem in fractal image compression is that of obtaining the IFS code (a set of linear transformations)which approximates a given image with a certain prescribed accuracy (inverse IFS problem).In this paper,we analyze and compare the performance of sharing and crowding niching techniques for identifying optimal selfsimilar transformations likely to represent a selfsimilar area within the image. The best results are found using the deterministic crowding method.We also present an nteractive Matlab program implementing the algorithms described in the paper.Facultad de Informátic

A comparison of diferent evolutive niching strategies for identifying a set of selfsimilar contractions for the IFS inverse problem

The key problem in fractal image compression is that of obtaining the IFS code (a set of linear transformations) which approximates a given image with a certain prescribed accuracy (inverse IFS problem). In this paper, we analyze and compare the performance of sharing and crowding niching techniques for identifying optimal selfsimilar transformations likely to represent a selfsimilar area within the image. The best results are found using the deterministic crowding method. We also present an interactive Matlab program implementing the algorithms described in the paperI Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Fractal Analysis

Fractal analysis is becoming more and more common in all walks of life. This includes biomedical engineering, steganography and art. Writing one book on all these topics is a very difficult task. For this reason, this book covers only selected topics. Interested readers will find in this book the topics of image compression, groundwater quality, establishing the downscaling and spatio-temporal scale conversion models of NDVI, modelling and optimization of 3T fractional nonlinear generalized magneto-thermoelastic multi-material, algebraic fractals in steganography, strain induced microstructures in metals and much more. The book will definitely be of interest to scientists dealing with fractal analysis, as well as biomedical engineers or IT engineers. I encourage you to view individual chapters

Approximation of the critical buckling factor for composite panels

This article is concerned with the approximation of the critical buckling factor for thin composite plates. A new method to improve the approximation of this critical factor is applied based on its behavior with respect to lamination parameters and loading conditions. This method allows accurate approximation of the critical buckling factor for non-orthotropic laminates under complex combined loadings (including shear loading). The influence of the stacking sequence and loading conditions is extensively studied as well as properties of the critical buckling factor behavior (e.g concavity over tensor D or out-of-plane lamination parameters). Moreover, the critical buckling factor is numerically shown to be piecewise linear for orthotropic laminates under combined loading whenever shear remains low and it is also shown to be piecewise continuous in the general case. Based on the numerically observed behavior, a new scheme for the approximation is applied that separates each buckling mode and builds linear, polynomial or rational regressions for each mode. Results of this approach and applications to structural optimization are presented