SEARCHING AND INDEXING DISTORTED DATA COLLECTIONS

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86091970" target="_blank" >RIV/61989100:27240/14:86091970 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/14:86091970

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

SEARCHING AND INDEXING DISTORTED DATA COLLECTIONS

Popis výsledku v původním jazyce

Success of many models and artificial intelligence methods strongly depends on ability to quickly and precisely search input data collection. Despite the existence of many algorithms for faster earching, the most of them fail while processing distorted input. Unfortunately, the distortion is natural for many types of data collections, especially for measurements of natural phenomena such as recipitations, river discharge volume etc. In this type of collections, there are no exact levels for generated values. This paper discusses possibilities of indexing and searching such distorted inputs and also proposes an alternative approach for their indexing. The proposed approach utilizes the Voting Experts algorithm for splitting the input regarding statistical indicators, the Dynamic Time Warping for dealing with distorted inaccuracies and hierarchical clustering for grouping similar sequences. Finally, the sample result of proposed algorithm applied on data collections consisting of measured river discharge volumes is shown.

Název v anglickém jazyce

SEARCHING AND INDEXING DISTORTED DATA COLLECTIONS

Popis výsledku anglicky

Success of many models and artificial intelligence methods strongly depends on ability to quickly and precisely search input data collection. Despite the existence of many algorithms for faster earching, the most of them fail while processing distorted input. Unfortunately, the distortion is natural for many types of data collections, especially for measurements of natural phenomena such as recipitations, river discharge volume etc. In this type of collections, there are no exact levels for generated values. This paper discusses possibilities of indexing and searching such distorted inputs and also proposes an alternative approach for their indexing. The proposed approach utilizes the Voting Experts algorithm for splitting the input regarding statistical indicators, the Dynamic Time Warping for dealing with distorted inaccuracies and hierarchical clustering for grouping similar sequences. Finally, the sample result of proposed algorithm applied on data collections consisting of measured river discharge volumes is shown.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

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

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

26th European Modeling and Simulation Symposium, EMSS 2014

ISBN

978-88-97999-32-4

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

301 - 306

Název nakladatele

Dime University of Genoa

Místo vydání

Genova

Místo konání akce

Bordeaux

Datum konání akce

10. 9. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—