Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm

This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. It addresses the limitations of the original Archimedes optimization algorithm (AOA) through two key modifications: rebalancing the explora...

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Bibliographic Details

Main Authors:	Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad
Format:	Article
Language:	en
Published:	Elsevier B.V. 2024
Subjects:	T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/43973/1/Data-driven%20continuous-time%20Hammerstein%20modeling%20with%20missing%20data.pdf http://umpir.ump.edu.my/id/eprint/43973/ https://doi.org/10.1016/j.rineng.2024.103357
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