Modeling with Fuzzy Transforms - a New Tool of Data Mining and Quantitative Finance

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F17%3AA1801P4K" target="_blank" >RIV/61988987:17610/17:A1801P4K - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Modeling with Fuzzy Transforms - a New Tool of Data Mining and Quantitative Finance

Popis výsledku v původním jazyce

The theory of fuzzy (F)-transforms relates to a modern mathematical modeling. It provides a (dimensionally) reduced and robust representation of original data. It is based on a granulation of a domain (fuzzy partition) and gives a tractable image of an original data. The main characteristics with respect to input data: size reduction, noise removal, invariance to geometrical transformations, knowledge transfer from conventional mathematics, fast computation. The F-transform has been applied to: image processing, computer vision, on-line pattern recognition in big data bases, time series analysis and forecasting, mathematical finance, numerical methods for differential equations, deep learning neural networks. In this contribution, we show that the technique of F-transforms fully agrees with the technique of dimensionality reduction, based on Laplacian eigenmaps. In the application part, we give an overview of the F-transform applications to mathematical finance.

Název v anglickém jazyce

Modeling with Fuzzy Transforms - a New Tool of Data Mining and Quantitative Finance

Popis výsledku anglicky

The theory of fuzzy (F)-transforms relates to a modern mathematical modeling. It provides a (dimensionally) reduced and robust representation of original data. It is based on a granulation of a domain (fuzzy partition) and gives a tractable image of an original data. The main characteristics with respect to input data: size reduction, noise removal, invariance to geometrical transformations, knowledge transfer from conventional mathematics, fast computation. The F-transform has been applied to: image processing, computer vision, on-line pattern recognition in big data bases, time series analysis and forecasting, mathematical finance, numerical methods for differential equations, deep learning neural networks. In this contribution, we show that the technique of F-transforms fully agrees with the technique of dimensionality reduction, based on Laplacian eigenmaps. In the application part, we give an overview of the F-transform applications to mathematical finance.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2017 6th Int. Conf. on Reliability, Infocom Technologies and Optimization (ICRITO)

ISBN

978-93-86238-31-3

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

17-21

Název nakladatele

Excellent Publishing House

Místo vydání

Amity University, Uttar Pradesh, Noida, India

Místo konání akce

Noida, India

Datum konání akce

20. 9. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—