Computation of Identification of a Gnostical Regression Model,
Robust to Both Input and Output Disturbances with the Help of
Parallel Computing–Basic Version

J 2018

Computation of Identification of a Gnostical Regression Model, Robust to Both Input and Output Disturbances with the Help of Parallel Computing–Basic Version

KNÍŽEK, Jiří, Lubomír PAVLIŠKA, Václav PROCHÁZKA, Adéla VRTKOVÁ, Ladislav BERÁNEK et. al.

Basic information

Original name

Computation of Identification of a Gnostical Regression Model, Robust to Both Input and Output Disturbances with the Help of Parallel Computing–Basic Version

Authors

KNÍŽEK, Jiří (203 Czech Republic, guarantor), Lubomír PAVLIŠKA (203 Czech Republic), Václav PROCHÁZKA (203 Czech Republic), Adéla VRTKOVÁ (203 Czech Republic), Ladislav BERÁNEK (203 Czech Republic), Pavel BOUCHAL (203 Czech Republic, belonging to the institution), Bořivoj VOJTĚŠEK (203 Czech Republic), Rudolf NENUTIL (203 Czech Republic) and Martin KUBA (203 Czech Republic, belonging to the institution)

Edition

International Journal of Mathematics and Computation™, CESER, 2018, 0974-5718

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10102 Applied mathematics

Country of publisher

India

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

RIV identification code

RIV/00216224:14310/18:00101548

Organization unit

Faculty of Science

Keywords in English

Gnostics; statistics; environment; health; non-statistical methods; regression

Abstract

V originále

Our paper describes a demonstration of Kovanic's physical concept of the robust evaluation of data uncertainty on some regression tasks, i.e. in a very practical way. Special techniques of computation during the solution of regression tasks are explained in detail here. Properties of particular tasks' solutions are demonstrated also by graphical figuration.

Links

GA17-05957S, research and development project

Name: Evaluace nových potenciálních cílů a inhibitorů pro blokování vývoje metastáz u luminálních A nádorů prsu

Investor: Czech Science Foundation

MUNI/A/1100/2017, interní kód MU

Name: Podpora biochemického výzkumu v roce 2018

Investor: Masaryk University, Category A

Citovat

KNÍŽEK, Jiří, Lubomír PAVLIŠKA, Václav PROCHÁZKA, Adéla VRTKOVÁ, Ladislav BERÁNEK, Pavel BOUCHAL, Bořivoj VOJTĚŠEK, Rudolf NENUTIL and Martin KUBA. Computation of Identification of a Gnostical Regression Model, Robust to Both Input and Output Disturbances with the Help of Parallel Computing–Basic Version. International Journal of Mathematics and Computation™. CESER, 2018, vol. 29, No 2, p. 29-58. ISSN 0974-5718.

@article{1484863,
   author = {Knížek, Jiří and Pavliška, Lubomír and Procházka, Václav and Vrtková, Adéla and Beránek, Ladislav and Bouchal, Pavel and Vojtěšek, Bořivoj and Nenutil, Rudolf and Kuba, Martin},
   article_number = {2},
   keywords = {Gnostics; statistics; environment; health; non-statistical methods; regression},
   language = {eng},
   issn = {0974-5718},
   journal = {International Journal of Mathematics and Computation™},
   title = {Computation of Identification of a Gnostical Regression Model, Robust to Both Input and Output Disturbances with the Help of Parallel Computing–Basic Version},
   url = {http://www.ceser.in/ceserp/index.php/ijmc/article/view/5491},
   volume = {29},
   year = {2018}
}

TY  - JOUR
ID  - 1484863
AU  - Knížek, Jiří - Pavliška, Lubomír - Procházka, Václav - Vrtková, Adéla - Beránek, Ladislav - Bouchal, Pavel - Vojtěšek, Bořivoj - Nenutil, Rudolf - Kuba, Martin
PY  - 2018
TI  - Computation of Identification of a Gnostical Regression Model, Robust to Both Input and Output Disturbances with the Help of Parallel Computing–Basic Version
JF  - International Journal of Mathematics and Computation™
VL  - 29
IS  - 2
SP  - 29-58
EP  - 29-58
PB  - CESER
SN  - 09745718
KW  - Gnostics
KW  - statistics
KW  - environment
KW  - health
KW  - non-statistical methods
KW  - regression
UR  - http://www.ceser.in/ceserp/index.php/ijmc/article/view/5491
N2  - Our paper describes a demonstration of Kovanic's physical concept of the robust evaluation of data uncertainty on some regression tasks, i.e. in a very practical way. Special techniques of computation during the solution of regression tasks are explained in detail here. Properties of particular tasks' solutions are demonstrated also by graphical figuration.
ER  -

KNÍŽEK, Jiří, Lubomír PAVLIŠKA, Václav PROCHÁZKA, Adéla VRTKOVÁ, Ladislav BERÁNEK, Pavel BOUCHAL, Bořivoj VOJTĚŠEK, Rudolf NENUTIL and Martin KUBA. Computation of Identification of a Gnostical Regression Model, Robust to Both Input and Output Disturbances with the Help of Parallel Computing–Basic Version. \textit{International Journal of Mathematics and Computation™}. CESER, 2018, vol.~29, No~2, p.~29-58. ISSN~0974-5718.

Detailed Information on Publication Record