A Predictive Modeling Based on Regression and Artificial Neural Network Analysis of Laser Transformation Hardening for Cylindrical Steel Workpieces

Network Analysis ◽

Predictive Modeling ◽

Neural Network Analysis ◽

Artificial Neural ◽

Cylindrical Steel ◽

Laser Transformation Hardening

1902: Is Steinstrasse After ESWL of Renal Stones Predictable? Artificial Neural Network Analysis

The Journal of Urology ◽

10.1016/s0022-5347(18)39094-3 ◽

2004 ◽

Vol 171 (4S) ◽

pp. 502-503

Author(s):

Mohamed A. Gomha ◽

Khaled Z. Sheir ◽

Saeed Showky ◽

Khaled Madbouly ◽

Emad Elsobky ◽

...

Keyword(s):

Neural Network ◽

Network Analysis ◽

Renal Stones ◽

Neural Network Analysis ◽

Multi-attribute and Artificial Neural Network Analysis of Seismic Inferred Chimney-like Features in Marine Sediments: A Study from KG Basin, India

Journal of the Geological Society of India ◽

10.1007/s12594-021-1672-8 ◽

2021 ◽

Vol 97 (3) ◽

pp. 238-242

Author(s):

Rowtu Ramu ◽

Kalachand Sain

Keyword(s):

Neural Network ◽

Network Analysis ◽

Marine Sediments ◽

Neural Network Analysis ◽

Prediction of limit pressure and pressuremeter modulus using artificial neural network analysis based on CPTU data

Arabian Journal of Geosciences ◽

10.1007/s12517-020-06324-4 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Meng Wu ◽

Surya Sarat Chandra Congress ◽

Lulu Liu ◽

Guojun Cai ◽

Wei Duan ◽

...

Keyword(s):

Neural Network ◽

Network Analysis ◽

Neural Network Analysis ◽

Limit Pressure ◽

Artificial Neural ◽

Pressuremeter Modulus

Urinary Symptoms and Urodynamic Findings in Women with Pelvic Organ Prolapse: Is There a Correlation? Results of an Artificial Neural Network Analysis

European Urology ◽

10.1016/j.eururo.2011.03.010 ◽

2011 ◽

Vol 60 (2) ◽

pp. 253-260 ◽

Cited By ~ 41

Author(s):

Maurizio Serati ◽

Stefano Salvatore ◽

Gabriele Siesto ◽

Elena Cattoni ◽

Andrea Braga ◽

...

Keyword(s):

Neural Network ◽

Pelvic Organ Prolapse ◽

Network Analysis ◽

Pelvic Organ ◽

Urinary Symptoms ◽

Neural Network Analysis ◽

Predicting the intracellular water compartment using artificial neural network analysis

Acta Diabetologica ◽

10.1007/s00592-003-0019-9 ◽

2003 ◽

Vol 40 (S1) ◽

pp. s15-s18 ◽

Cited By ~ 2

Author(s):

E. I. Mohamed ◽

C. Maiolo ◽

R. Linder ◽

S. J. Pöppl ◽

A. De Lorenzo

Keyword(s):

Neural Network ◽

Network Analysis ◽

Intracellular Water ◽

Neural Network Analysis ◽

Water Compartment ◽

The Corrosion of Rebar in Concrete. Part III: Artificial Neural Network Analysis of Chloride Threshold Data

Corrosion Science ◽

10.1016/j.corsci.2021.109438 ◽

2021 ◽

pp. 109438

Author(s):

Yakun Zhu ◽

Digby D. Macdonald ◽

Jie Qiu ◽

Mirna Urquidi-Macdonald

Keyword(s):

Neural Network ◽

Network Analysis ◽

Neural Network Analysis ◽

Chloride Threshold ◽

Threshold Data ◽

Concrete Part ◽

Predicting student performance using artificial neural network analysis

Medical Education ◽

10.1111/j.1365-2923.2008.03052.x ◽

2008 ◽

Vol 42 (5) ◽

pp. 516-517 ◽

Cited By ~ 5

Author(s):

Ben van Heerden ◽

Chris Aldrich ◽

Alten du Plessis

Keyword(s):

Neural Network ◽

Network Analysis ◽

Student Performance ◽

Neural Network Analysis ◽

Artificial Neural ◽

Predicting Student Performance

An artificial neural network analysis of porcine pancreas lipase catalysed esterification of anthranilic acid with methanol

Process Biochemistry ◽

10.1016/j.procbio.2005.03.045 ◽

2005 ◽

Vol 40 (10) ◽

pp. 3372-3376 ◽

Cited By ~ 37

Author(s):

Balaraman Manohar ◽

Soundar Divakar

Keyword(s):

Neural Network ◽

Network Analysis ◽

Anthranilic Acid ◽

Neural Network Analysis ◽

Porcine Pancreas ◽

Porcine Pancreas Lipase ◽

Proceedings of the 2017 2nd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2017) ◽

Finite Element and Artificial Neural Network Analysis of Thin-Walled Steel Perforated Sections in Compression

10.2991/eame-17.2017.37 ◽

2017 ◽

Author(s):

Meng Wu ◽

Zhijun Lyu ◽

Qian Xiang ◽

Yiming Song ◽

Hongliang Li

Keyword(s):

Neural Network ◽

Finite Element ◽

Network Analysis ◽

Neural Network Analysis ◽

Thin Walled ◽

Modeling of quaternary dyes adsorption onto ZnO–NR–AC artificial neural network: Analysis by derivative spectrophotometry

Journal of Industrial and Engineering Chemistry ◽

10.1016/j.jiec.2015.11.010 ◽

2016 ◽

Vol 34 ◽

pp. 186-197 ◽

Cited By ~ 159

Author(s):

E. Alipanahpour Dil ◽

M. Ghaedi ◽

A.M. Ghaedi ◽

A. Asfaram ◽

A. Goudarzi ◽

...

Keyword(s):

Neural Network ◽

Network Analysis ◽

Derivative Spectrophotometry ◽

Neural Network Analysis ◽

Artificial Neural ◽

Dyes Adsorption