Parameters Estimation of a Lotka-Volterra Model in an Application for Market Graphics Processing Units

Dzhakhongir Normatov; Paolo Mercorelli

doi:10.15439/2022F61

Parameters Estimation of a Lotka-Volterra Model in an Application for Market Graphics Processing Units

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Standard

Parameters Estimation of a Lotka-Volterra Model in an Application for Market Graphics Processing Units. / Normatov, Dzhakhongir; Mercorelli, Paolo.

Proceedings of the 17th Conference on Computer Science and Intelligence Systems. ed. / Maria Ganzha; Leszek Maciaszek; Marcin Paprzycki; Dominik Slezak. Warsaw : Polish Information Processing Society, 2022. p. 935-938 (Annals of Computer Science and Information System; Vol. 30).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Harvard

Normatov, D & Mercorelli, P 2022, Parameters Estimation of a Lotka-Volterra Model in an Application for Market Graphics Processing Units. in M Ganzha, L Maciaszek, M Paprzycki & D Slezak (eds), Proceedings of the 17th Conference on Computer Science and Intelligence Systems. Annals of Computer Science and Information System, vol. 30, Polish Information Processing Society, Warsaw, pp. 935-938, Conference - 17th Conference on Computer Science and Intelligence Systems, Sofia, Bulgaria, 04.09.22. https://doi.org/10.15439/2022F61

APA

Normatov, D., & Mercorelli, P. (2022). Parameters Estimation of a Lotka-Volterra Model in an Application for Market Graphics Processing Units. In M. Ganzha, L. Maciaszek, M. Paprzycki, & D. Slezak (Eds.), Proceedings of the 17th Conference on Computer Science and Intelligence Systems (pp. 935-938). (Annals of Computer Science and Information System; Vol. 30). Polish Information Processing Society. https://doi.org/10.15439/2022F61

Vancouver

Normatov D, Mercorelli P. Parameters Estimation of a Lotka-Volterra Model in an Application for Market Graphics Processing Units. In Ganzha M, Maciaszek L, Paprzycki M, Slezak D, editors, Proceedings of the 17th Conference on Computer Science and Intelligence Systems. Warsaw: Polish Information Processing Society. 2022. p. 935-938. (Annals of Computer Science and Information System). doi: 10.15439/2022F61

Bibtex

@inbook{ba74b1a144584c4495081fe4b52e79ef,

title = "Parameters Estimation of a Lotka-Volterra Model in an Application for Market Graphics Processing Units",

abstract = "In this paper, a least squares method is used to estimate parameter values in the Lotka-Volterra model. The data used are graphics processing units (GPU) shipment worldwide by three key competitors, namely Nvidia, Intel, AMD. The goal is to quantify the parameter values of a model with minimal error in order to qualitatively solve the problem and fit the raw data as closely as possible. Based on the real measurements, the predator between the competitors is recognized through the identification procedure comparing the sign of the coefficients with the original Lotka-Volterra model structure.",

keywords = "Engineering, Computer Science, Parameter estimation, computational modeling, Graphics processing units, Estimation, Data models, Least mean squares methods",

author = "Dzhakhongir Normatov and Paolo Mercorelli",

note = "Publisher Copyright: {\textcopyright} 2022 Polish Information Processing Society.; Conference - 17th Conference on Computer Science and Intelligence Systems, FedCSIS 2022 ; Conference date: 04-09-2022 Through 07-09-2022",

year = "2022",

month = sep,

day = "26",

doi = "10.15439/2022F61",

language = "English",

isbn = "9788396589712",

series = "Annals of Computer Science and Information System",

publisher = "Polish Information Processing Society",

pages = "935--938",

editor = "Maria Ganzha and Leszek Maciaszek and Marcin Paprzycki and Dominik Slezak",

booktitle = "Proceedings of the 17th Conference on Computer Science and Intelligence Systems",

address = "Poland",

url = "https://fedcsis.org/2022/node",

}

RIS

TY - CHAP

T1 - Parameters Estimation of a Lotka-Volterra Model in an Application for Market Graphics Processing Units

AU - Normatov, Dzhakhongir

AU - Mercorelli, Paolo

N1 - Conference code: 17

PY - 2022/9/26

Y1 - 2022/9/26

N2 - In this paper, a least squares method is used to estimate parameter values in the Lotka-Volterra model. The data used are graphics processing units (GPU) shipment worldwide by three key competitors, namely Nvidia, Intel, AMD. The goal is to quantify the parameter values of a model with minimal error in order to qualitatively solve the problem and fit the raw data as closely as possible. Based on the real measurements, the predator between the competitors is recognized through the identification procedure comparing the sign of the coefficients with the original Lotka-Volterra model structure.

AB - In this paper, a least squares method is used to estimate parameter values in the Lotka-Volterra model. The data used are graphics processing units (GPU) shipment worldwide by three key competitors, namely Nvidia, Intel, AMD. The goal is to quantify the parameter values of a model with minimal error in order to qualitatively solve the problem and fit the raw data as closely as possible. Based on the real measurements, the predator between the competitors is recognized through the identification procedure comparing the sign of the coefficients with the original Lotka-Volterra model structure.

KW - Engineering

KW - Computer Science

KW - Parameter estimation

KW - computational modeling

KW - Graphics processing units

KW - Estimation

KW - Data models

KW - Least mean squares methods

UR - http://www.scopus.com/inward/record.url?scp=85141144048&partnerID=8YFLogxK

UR - https://ieeexplore.ieee.org/xpl/conhome/9908518/proceeding

UR - https://ieeexplore.ieee.org/document/9909348

UR - https://www.mendeley.com/catalogue/2b5f25a1-ebf7-332f-82b5-46b9f707ee95/

U2 - 10.15439/2022F61

DO - 10.15439/2022F61

M3 - Article in conference proceedings

AN - SCOPUS:85141144048

SN - 9788396589712

T3 - Annals of Computer Science and Information System

SP - 935

EP - 938

BT - Proceedings of the 17th Conference on Computer Science and Intelligence Systems

A2 - Ganzha, Maria

A2 - Maciaszek, Leszek

A2 - Paprzycki, Marcin

A2 - Slezak, Dominik

PB - Polish Information Processing Society

CY - Warsaw

T2 - Conference - 17th Conference on Computer Science and Intelligence Systems

Y2 - 4 September 2022 through 7 September 2022

ER -

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