Modeling of complex systems for softcomputing methods
Project goals
The goal of the project is theoretical analysis of properties of softcomputing computational models suitable for processing of high-dimensional complex data from point of view of minimization of model complexity, efectivity of learning and capability ofgeneralization. Further goal is application of theoretical results to design of hybrid algorithms of methalearning with adaptive choices of models and their parameters and implementation of these algorithms as Java and MATLAB software tools and their testing on real data.
Keywords
softcomputing computational modelsmodel complexityadaptive and hybrid learning algorithmsmethalearninggeneralization
Public support
Provider
Ministry of Education, Youth and Sports
Programme
COST CZ
Call for proposals
COST CZ 3 (SMSM2013LD3)
Main participants
Ústav informatiky AV ČR, v. v. i.
Contest type
VS - Public tender
Contract ID
MSMT-9339/2013-311
Alternative language
Project name in Czech
Modelování složitých systémů softcomputingovými metodami
Annotation in Czech
Cílem projektu je teoretická analýza vlastností softcomputingových výpočetních modelů vhodných pro zpracování vysoce dimenzionálních složitých dat z hlediska minimalizace modelové složitosti, efektivity učení a schopnosti generalizace. Dále je to využitíteoretických výsledků pro návrh hybridních algoritmů metaučení s adaptivní volbou výpočetního modelu a jeho parametrů a implementace těchto algoritmů jako softwarového nástroje v prostředí Java a MATLAB a jejich testování.
Scientific branches
R&D category
ZV - Basic research
CEP classification - main branch
IN - Informatics
CEP - secondary branch
BA - General mathematics
CEP - another secondary branch
JC - Computer hardware and software
10101 - Pure mathematics
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
20206 - Computer hardware and architecture
Completed project evaluation
Provider evaluation
V - Vynikající výsledky projektu (s mezinárodním významem atd.)
Project results evaluation
Estimates of model complexity of neural networks suitable for processing big high-dimensional data were derived. Hybrid learning algorithms based on theoretical results were developed. The algorithms were implemented and tested on benchmarks and real sensor data from partners from the project EuNetAir.
Solution timeline
Realization period - beginning
Mar 21, 2013
Realization period - end
Nov 15, 2016
Project status
U - Finished project
Latest support payment
Feb 24, 2016
Data delivery to CEP
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data delivery code
CEP17-MSM-LD-U/01:1
Data delivery date
Jun 23, 2017
Finance
Total approved costs
2,199 thou. CZK
Public financial support
1,247 thou. CZK
Other public sources
952 thou. CZK
Non public and foreign sources
0 thou. CZK
Recognised costs
2 199 CZK thou.
Public support
1 247 CZK thou.
0%
Provider
Ministry of Education, Youth and Sports
CEP
IN - Informatics
Solution period
21. 03. 2013 - 15. 11. 2016