Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)

Linear Regression Approach to Fuzzy Cognitive Maps with History Data

Authors
Vesa A. Niskanen
Corresponding Author
Vesa A. Niskanen
Available Online 30 August 2021.
DOI
10.2991/asum.k.210827.045How to use a DOI?
Keywords
Fuzzy cognitive maps, History data, Linear regression analysis, Quantitative human sciences
Abstract

Methods of linear regression analysis are applied to fuzzy cognitive map construction according to history data from the standpoint of quantitative human sciences. When the linearized version of history data is also used, this construction may be reduced to ordinary linear regression analysis. This linearization applies the inverted transformation functions of the fuzzy cognitive maps. Our approach will avoid subjective reasoning and interpretation on these model outcomes by relying on the objective and well-justified statistical theories instead.

Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Cite this article

TY  - CONF
AU  - Vesa A. Niskanen
PY  - 2021
DA  - 2021/08/30
TI  - Linear Regression Approach to Fuzzy Cognitive Maps with History Data
BT  - Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)
PB  - Atlantis Press
SP  - 338
EP  - 344
SN  - 2589-6644
UR  - https://doi.org/10.2991/asum.k.210827.045
DO  - 10.2991/asum.k.210827.045
ID  - Niskanen2021
ER  -