An Approach to Restoring Missing Data in an Experimental Sample-Reference-Cited by-同舟云学术

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An Approach to Restoring Missing Data in an Experimental Sample

Published:2022-11-10 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 17th International Conference on Computer Sciences and Information Technologies (CSIT)
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Author:

Bulgakova Oleksandra¹,Stepashko Volodymyr²,Zosimov Viacheslav¹

Affiliation:

1. Taras Shevchenko National University of Kyiv,Department of Applied information systems,Kyiv,Ukraine

2. International research and training centre for information technologies and systems of the NAS and MES of Ukraine,Department for Information technologies of inductive modeling,Kyiv,Ukraine

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10000061/10000064/10000588.pdf?arnumber=10000588

Reference20 articles.

1. Advances in GMDH-based Predictive Analytics Tools for Business Intelligence Systems;yefimenko;Proc Int Conf on Advances in Computer Information Technologies ACIT-2018 Ceske Budejovice,2018

2. Inductive modeling from historical perspective

3. Inductive sorting-out GMDH algorithms with polynomial complexity for active neurons of neural network

4. Robust Polynomial Neural Network in Quantative-Structure Activity Relationship Studies;aksyonova;Systems Analysis Modeling Simulation,2003

5. GMDH and Neural Network Application for Modeling Vital Functions of Green Algae under Toxic Impact;bulgakova;2nd International Conference on Inductive Modelling Kyiv IRTC ITS NASU,2008

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