Improvements of real coded genetic algorithms based on differential operators preventing premature convergence

This paper presents several types of evolutionary algorithms (EAs) used for global optimization on real domains. The interest has been focused on multimodal problems, where the difficulties of a premature convergence usually occurs. First the standard genetic algorithm (SGA) using binary encoding of real values and its unsatisfactory behavior with multimodal problems is briefly reviewed together with some improvements of fighting premature convergence. Two types of real encoded methods based on differential operators are examined in detail: the differential evolution (DE), a very modern and effective method firstly published by R. Storn and K. Price, and the simplified real-coded differential genetic algorithm SADE proposed by the authors. In addition, an improvement of the SADE method, called CERAF technology, enabling the population of solutions to escape from local extremes, is examined. All methods are tested on an identical set of objective functions and a systematic comparison based on a reliable methodology is presented. It is confirmed that real coded methods generally exhibit better behavior on real domains than the binary algorithms, even when extended by several improvements. Furthermore, the positive influence of the differential operators due to their possibility of self-adaptation is demonstrated. From the reliability point of view, it seems that the real encoded differential algorithm, improved by the technology described in this paper, is a universal and reliable method capable of solving all proposed test problems.Comment: 23 pages, 2 figures, 4 table

Intelligent Surveillance Algorithms for Harbor Security

katedra kybernetik

Lipidomické profilování lidského séra umožňující detekci karcinomu slinivky břišní

Pancreatic cancer has the worst prognosis among all cancers. Cancer screening of body fluids may improve the survival time prognosis of patients, who are often diagnosed too late at an incurable stage. Several studies report the dysregulation of lipid metabolism in tumor cells, suggesting that changes in the blood lipidome may accompany tumor growth. Here we show that the comprehensive mass spectrometric determination of a wide range of serum lipids reveals statistically significant differences between pancreatic cancer patients and healthy controls, as visualized by multivariate data analysis. Three phases of biomarker discovery research (discovery, qualification, and verification) are applied for 830 samples in total, which shows the dysregulation of some very long chain sphingomyelins, ceramides, and (lyso) phosphatidylcholines. The sensitivity and specificity to diagnose pancreatic cancer are over 90%, which outperforms CA 19-9, especially at an early stage, and is comparable to established diagnostic imaging methods. Furthermore, selected lipid species indicate a potential as prognostic biomarkers.Rakovina slinivky má nejhorší prognózu ze všech nádorů. Screening nádorových onemocnění tělními tekutinami může zlepšit časovou prognózu přežití pacientů, kteří jsou často diagnostikováni příliš pozdě v nevyléčitelném stadiu. Několik studií uvádí dysregulaci metabolismu lipidů v nádorových buňkách, což naznačuje, že změny v krevním lipidomu mohou doprovázet růst nádoru. Zde ukazujeme, že komplexní hmotnostní spektrometrické stanovení širokého spektra sérových lipidů odhaluje statisticky významné rozdíly mezi pacienty s rakovinou pankreatu a zdravými kontrolami, jak je vizualizováno multivariační analýzou dat. Tři fáze výzkumu v oblasti objevování biomarkerů (objev, kvalifikace a verifikace) jsou aplikovány celkem na 830 vzorků, což prokazuje dysregulaci některých velmi dlouhých řetězců sfingomyelinů, ceramidů a (lyso)fosfatidylcholinů. Senzitivita a specificita k diagnostice karcinomu slinivky břišní je více než 90%, což překonává CA 19-9, zejména v raném stadiu, a je srovnatelná se zavedenými diagnostickými zobrazovacími metodami. Vybrané druhy lipidů navíc indikují potenciál jako prognostické biomarkery