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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

Authors

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.

Original languageEnglish
Title of host publicationProceedings of the 17th Conference on Computer Science and Intelligence Systems
EditorsMaria Ganzha, Leszek Maciaszek, Marcin Paprzycki, Dominik Slezak
Number of pages4
Place of PublicationWarsaw
PublisherPolish Information Processing Society
Publication date26.09.2022
Pages935-938
ISBN (print)9788396589712
ISBN (electronic)978-83-965897-1-2, 978-83-965897-0-5, 978-83-962423-9-6
DOIs
Publication statusPublished - 26.09.2022
EventConference - 17th Conference on Computer Science and Intelligence Systems - Hybrid / NATO Crisis Management and Disaster Response Centre of Excellence , Sofia, Bulgaria
Duration: 04.09.2022 → 07.09.2022
Conference number: 17
https://fedcsis.org/2022/node

Bibliographical note

Publisher Copyright:
© 2022 Polish Information Processing Society.

    Research areas

  • Engineering - Computer Science, Parameter estimation, computational modeling, Graphics processing units, Estimation, Data models, Least mean squares methods

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A Fluid Elastomeric Actuator Design for Soft Robots

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An innovative efficiency of incubator to enhance organization supportive business using machine learning approach

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An Over-Actuated Hexacopter Tilt-Rotor UAV Prototype for Agriculture of Precision: Modeling and Control

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Rigon, S., Haus, B., Mercorelli, P. & Zigliotto, M., 27.02.2025, In: IEEE Open Journal of Power Electronics. 6, p. 734-746 13 p.

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