A study on genetic algorithm to select architecture of a optimal neural network in the hot rolling process

Son, Joon-Sik; Lee, D.M.; Kim, I.S.; Choi, Seung-Gap

doi:10.1016/j.jmatprotec.2004.04.376

Cited by 55 publications

(22 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The same model is utilized for simulation by applying Genetic algorithms (Son et al, 2004). Results obtained are shown in Fig.…”

Section: Discussionmentioning

confidence: 99%

Decoupling and Linearizing of a pH Plant using Hirschornâs and Genetic Algorithms

P.¹

2012

Journal of Computer Science

View full text Add to dashboard Cite

Problem statement:This study is to maintain the interacting liquid level and pH parameter at a desired value. The purpose of decoupling and linearization algorithm is to prevent interaction and making the system linear. Approach: In this study Hirchorn's and Genetic Algorithms (GA) are proposed to make the system linear, non interacting system. This study presents the performance comparison of Hirschorn's (decoupling and linearization algorithm) and Genetic Algorithms (GA) for a approximated model of Interacting level and pH non-linear process. Results: Closed loop simulation was carried out incorporating the above algorithm and the results are compared. Control performance with Hirschorn's is found to give better results than with GA. Conclusion: This study demonstrates the effectiveness of Hirchorn's algorithm in MIMO nonlinear interacting process. Obtained control laws for Hirschorn's algorithm give improved values for Settling Time (Ts) and Integral Square Error (ISE).

show abstract

“…The same model is utilized for simulation by applying Genetic algorithms (Son et al, 2004). Results obtained are shown in Fig.…”

Section: Discussionmentioning

confidence: 99%

Decoupling and Linearizing of a pH Plant using Hirschornâs and Genetic Algorithms

P.¹

2012

Journal of Computer Science

View full text Add to dashboard Cite

show abstract

“…To define input layer neurons number which are equal to auto regressive vector rank in ARMA method, the rank of auto regressive (p) and mobile mean (q) are implemented based on proposed method of Son et al (2004). Finally, the validity of model has been checked by comparing between anticipated added value by the model and measured values based on some of the statistical years, which has not been used in network training.…”

Section: Fig 1 Single Input Neuron Modelmentioning

confidence: 99%

An application of artificial neural network to predict the added value of oil, gas and petroleum industry products

Vazifehdust¹,

Ashtiani²,

Mobarhan³

2013

10.5267/j.msl

View full text Add to dashboard Cite

“…Reference [3] developed a predicted model of rolling force using neural network and genetic algorithm (GA) to improve the prediction accuracy of rolling force. Here GA was employed for the search of optimal neural network architecture.…”

Section: Introductionmentioning

confidence: 99%

An Online Algorithm for Roll Eccentricity Compensation

Zhang¹,

Wang²

2016

IJUNESST

View full text Add to dashboard Cite

show abstract

A study on genetic algorithm to select architecture of a optimal neural network in the hot rolling process

Cited by 55 publications

References 4 publications

Decoupling and Linearizing of a pH Plant using Hirschornâs and Genetic Algorithms

Decoupling and Linearizing of a pH Plant using Hirschornâs and Genetic Algorithms

An application of artificial neural network to predict the added value of oil, gas and petroleum industry products

An Online Algorithm for Roll Eccentricity Compensation

Contact Info

Product

Resources

About

A study on genetic algorithm to select architecture of a optimal neural network in the hot rolling process

Cited by 55 publications

References 4 publications

Decoupling and Linearizing of a pH Plant using Hirschornâs and Genetic Algorithms

Decoupling and Linearizing of a pH Plant using Hirschornâs and Genetic Algorithms

An application of artificial neural network to predict the added value of oil, gas and petroleum industry products

An Online Algorithm for Roll Eccentricity Compensation

Contact Info

Product

Resources

About

Decoupling and Linearizing of a pH Plant using Hirschornâs and Genetic Algorithms

Decoupling and Linearizing of a pH Plant using Hirschornâs and Genetic Algorithms