Grip strength prediction for Malaysian industrial workers using artificial neural networks

International Journal of Industrial Ergonomics ◽

10.1016/j.ergon.2004.11.006 ◽

2005 ◽

Vol 35 (9) ◽

pp. 807-816 ◽

Author(s):

Z. Taha ◽

Nazaruddin

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Grip Strength ◽

Strength Prediction ◽

Industrial Workers ◽

Artificial Neural

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Formulating grip strength and key pinch strength prediction models for Taiwanese: a comparison between stepwise regression and artificial neural networks

Journal of Ambient Intelligence and Humanized Computing ◽

10.1007/s12652-014-0245-8 ◽

2014 ◽

Vol 6 (1) ◽

pp. 37-46 ◽

Author(s):

Peng-Cheng Sung ◽

Chun-Chin Hsu ◽

Cheng-Lung Lee ◽

Yuan-Shyi Peter Chiu ◽

Huey-Long Chen

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Grip Strength ◽

Stepwise Regression ◽

Prediction Models ◽

Strength Prediction ◽

Pinch Strength ◽

Artificial Neural

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Failure strength prediction of unidirectional tensile coupons using acoustic emission peak amplitude and energy parameter with artificial neural networks

Composites Science and Technology ◽

10.1016/j.compscitech.2009.02.014 ◽

2009 ◽

Vol 69 (7-8) ◽

pp. 1151-1155 ◽

Author(s):

T. Sasikumar ◽

S. RajendraBoopathy ◽

K.M. Usha ◽

E.S. Vasudev

Keyword(s):

Neural Networks ◽

Acoustic Emission ◽

Artificial Neural Networks ◽

Energy Parameter ◽

Emission Peak ◽

Peak Amplitude ◽

Strength Prediction ◽

Failure Strength ◽

Artificial Neural

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Macrocell electric field strength prediction model based upon artificial neural networks

IEEE Journal on Selected Areas in Communications ◽

10.1109/jsac.2002.801217 ◽

2002 ◽

Vol 20 (6) ◽

pp. 1170-1177 ◽

Author(s):

A. Neskovic ◽

N. Neskovic ◽

D. Paunovic

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Field Strength ◽

Electric Field ◽

Prediction Model ◽

Electric Field Strength ◽

Strength Prediction ◽

Model Based ◽

Artificial Neural

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Microcell electric field strength prediction model based upon artificial neural networks

AEU - International Journal of Electronics and Communications ◽

10.1016/j.aeue.2009.05.005 ◽

2010 ◽

Vol 64 (8) ◽

pp. 733-738 ◽

Author(s):

Aleksandar Neskovic ◽

Natasa Neskovic

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Field Strength ◽

Electric Field ◽

Prediction Model ◽

Electric Field Strength ◽

Strength Prediction ◽

Model Based ◽

Artificial Neural

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Compression After Impact Strength Prediction in Composites Using Acoustic Emission and Artificial Neural Networks

49th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference <br> 16th AIAA/ASME/AHS Adaptive Structures Conference<br> 10t ◽

10.2514/6.2008-2257 ◽

2008 ◽

Author(s):

Eric Hill ◽

Yi Zhao ◽

Tom Ebert ◽

Jonathan Kay ◽

Gregory Lewis

Keyword(s):

Neural Networks ◽

Acoustic Emission ◽

Artificial Neural Networks ◽

Impact Strength ◽

Strength Prediction ◽

Compression After Impact ◽

Artificial Neural

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Unconfined compressive strength prediction of soils stabilized using artificial neural networks and support vector machines

Frontiers of Structural and Civil Engineering ◽

10.1007/s11709-021-0689-9 ◽

2021 ◽

Author(s):

Alireza Tabarsa ◽

Nima Latifi ◽

Abdolreza Osouli ◽

Younes Bagheri

Keyword(s):

Neural Networks ◽

Compressive Strength ◽

Artificial Neural Networks ◽

Support Vector Machines ◽

Unconfined Compressive Strength ◽

Strength Prediction ◽

Support Vector ◽

Vector Machines ◽

Artificial Neural

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Empirical estimation of the grades of hearing impairment among industrial workers based on new artificial neural networks and classical regression methods

Indian Journal of Occupational and Environmental Medicine ◽

10.4103/0019-5278.165337 ◽

2015 ◽

Vol 19 (2) ◽

pp. 84 ◽

Author(s):

Mohsen Aliabadi ◽

Maryam Farhadian ◽

Ebrahim Darvishi

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Hearing Impairment ◽

Industrial Workers ◽

Empirical Estimation ◽

Regression Methods ◽

Artificial Neural ◽

Classical Regression

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Compressive strength prediction of environmentally friendly concrete using artificial neural networks

Journal of Building Engineering ◽

10.1016/j.jobe.2018.01.007 ◽

2018 ◽

Vol 16 ◽

pp. 213-219 ◽

Author(s):

Hosein Naderpour ◽

Amir Hossein Rafiean ◽

Pouyan Fakharian

Keyword(s):

Neural Networks ◽

Compressive Strength ◽

Artificial Neural Networks ◽

Environmentally Friendly ◽

Strength Prediction ◽

Artificial Neural

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Strength Prediction of High-Strength Concrete by Fuzzy Logic and Artificial Neural Networks

Journal of Materials in Civil Engineering ◽

10.1061/(asce)mt.1943-5533.0000985 ◽

2014 ◽

Vol 26 (11) ◽

pp. 04014079 ◽

Author(s):

Gökmen Tayfur ◽

Tahir Kemal Erdem ◽

Önder Kırca

Keyword(s):

Neural Networks ◽

Fuzzy Logic ◽

Artificial Neural Networks ◽

High Strength Concrete ◽

High Strength ◽

Strength Prediction ◽

Strength Concrete ◽

Artificial Neural

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Artificial Neural Networks (ANN) Based Compressive Strength Prediction of AFRP Strengthened Steel Tube

International Journal of Steel Structures ◽

10.1007/s13296-019-00276-6 ◽

2019 ◽

Vol 20 (1) ◽

pp. 156-174 ◽

Author(s):

Abderrahim Djerrad ◽

Feng Fan ◽

Xu-dong Zhi ◽

Qi-jian Wu

Keyword(s):

Neural Networks ◽

Compressive Strength ◽

Artificial Neural Networks ◽

Strength Prediction ◽

Artificial Neural

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