Research on Self Adjustment Technology of Data Mining Algorithm in Control Engineering

Chunxiang Huang, Nenjun Ben, Guojun Yan

2025

Abstract

The research direction is the self-tuning technology of data mining algorithm in control engineering. The main purpose of this research is to develop a new technology of automatic fault identification and diagnosis in various industrial systems based on nonlinear models. The proposed method will be used to optimize such systems through neural networks. The results obtained in the implementation stage show that the neural network with a large number of hidden units (up to 500) can be used as an effective tool to solve nonlinear model problems. The research on self-tuning technology of data mining algorithm in control engineering is to find the best method of using data mining algorithm to control the process. It is also called intelligent system or artificial intelligence (AI). The main goal of this research is to develop an intelligent system that can perform better than human operators in the control process. Self tuning technology refers to the ability of computer systems to learn from past experience and improve performance by using these experiences without any human intervention.

Paper Citation

in Harvard Style

Huang C., Ben N. and Yan G. (2025). Research on Self Adjustment Technology of Data Mining Algorithm in Control Engineering. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 453-456. DOI: 10.5220/0013545400004664

in Bibtex Style

@conference{incoft25,
author={Chunxiang Huang and Nenjun Ben and Guojun Yan},
title={Research on Self Adjustment Technology of Data Mining Algorithm in Control Engineering},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT},
year={2025},
pages={453-456},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013545400004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT
TI - Research on Self Adjustment Technology of Data Mining Algorithm in Control Engineering
SN - 978-989-758-763-4
AU - Huang C.
AU - Ben N.
AU - Yan G.
PY - 2025
SP - 453
EP - 456
DO - 10.5220/0013545400004664
PB - SciTePress