Döntéstámogatás fuzzy módszerekkel, optimalizálással = Decision support with fuzzy methods and optimization.

2003 és 2006 közt kutatásokat két irányban folytattam: fuzzy osztályozás és optimalizálás evolúciós algoritmussal (EA). A fuzzy témakörben egy EA alapú fuzzy osztályozó algoritmust publikáltam. Az optimalizálás témakörben több algoritmust fejlesztettem, melyek különböző EA struktúrákat, ill. memória alapú technikákat alkalmaztak. Több skalár optimalizálás algoritmust publikáltam: nem-lineáris problémák, kombinatorikus optimalizálás (QAP, 3-SAT, BQP, TSP). Vektoroptimalizálás témakörben algoritmusaim: nem-lineáris optimalizálás, kombinatorikus problémák (QAP, TSP). Több algoritmusom eredménye hasonló, vagy jobb minőségű, mint a megjelenéskor ismert más EA módszerek eredménye. | Between 2003 and 2006 my research had two directions: fuzzy classification and optimization with evolutionary algorithm (EA). In the fuzzy topic I published a fuzzy classification algorithm based on EA. In the optimization topic I developed algorithms with different EA structures and used memory based techniques. I published more single-objective algorithms, e.g. non-linear optimization with parallel EAs, combinatorial optimization (QAP, 3-SAT, BQP, TSP). I published some multi-objective algorithms: a non-linear optimization method and combinatorial optimization (QAP, TSP). By some of my published algorithms the results had similar or better quality than the other EA in the same topics

A Survey on Soft Subspace Clustering

Subspace clustering (SC) is a promising clustering technology to identify clusters based on their associations with subspaces in high dimensional spaces. SC can be classified into hard subspace clustering (HSC) and soft subspace clustering (SSC). While HSC algorithms have been extensively studied and well accepted by the scientific community, SSC algorithms are relatively new but gaining more attention in recent years due to better adaptability. In the paper, a comprehensive survey on existing SSC algorithms and the recent development are presented. The SSC algorithms are classified systematically into three main categories, namely, conventional SSC (CSSC), independent SSC (ISSC) and extended SSC (XSSC). The characteristics of these algorithms are highlighted and the potential future development of SSC is also discussed.Comment: This paper has been published in Information Sciences Journal in 201

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