Development of a High-Precision Machining Center Using Neural Networks and Genetic Algorithm.

TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C ◽

10.1299/kikaic.61.4517 ◽

1995 ◽

Vol 61 (591) ◽

pp. 4517-4522 ◽

Author(s):

Mamoru Mitsuishi ◽

Tsutomu Okumura ◽

Naohiko Sugita ◽

Takaaki Nagao ◽

Yotaro Hatamura

Keyword(s):

Genetic Algorithm ◽

Neural Networks ◽

High Precision ◽

Precision Machining ◽

Machining Center

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Modelling and experimental investigation of spindle and cutter dynamics for a high-precision machining center

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-003-1794-8 ◽

2004 ◽

Vol 24 (11-12) ◽

pp. 806-815 ◽

Author(s):

Adam G. Rehorn ◽

Jin Jiang ◽

Peter E. Orban ◽

Evgueni Bordatchev

Keyword(s):

Experimental Investigation ◽

High Precision ◽

Precision Machining ◽

Machining Center

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Development and Evaluation of a High-Precision Machining Center with Friction-Less Drives

Towards Synthesis of Micro-/Nano-systems ◽

10.1007/1-84628-559-3_27 ◽

2006 ◽

pp. 163-167

Author(s):

Daisuke Kono ◽

Atsushi Matsubara ◽

Soichi Ibaraki ◽

Hisashi Otsubo ◽

Masaru Tsuboi ◽

...

Keyword(s):

High Precision ◽

Precision Machining ◽

Machining Center

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High Precision Machining with Multi-flute End-mill tool on 5-Axis Controlled Machining Center. Achievement of Constant Cutting Force in Side milling by Controlling Axial Depth of Cut.

Journal of the Japan Society for Precision Engineering ◽

10.2493/jjspe.69.385 ◽

2003 ◽

Vol 69 (3) ◽

pp. 385-389 ◽

Author(s):

Heisaburo NAKAGAWA ◽

Toshiki HIROGAKI ◽

Maiko NAKAYAMA ◽

Hirotoshi OHTSUKA ◽

Yoshiaki KAKINO ◽

...

Keyword(s):

Cutting Force ◽

High Precision ◽

Precision Machining ◽

Depth Of Cut ◽

End Mill ◽

Side Milling ◽

Machining Center ◽

Constant Cutting Force ◽

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Development of High Precision Machining Center "Zμ3500"

Journal of the Japan Society for Precision Engineering ◽

10.2493/jjspe.72.681 ◽

2006 ◽

Vol 72 (6) ◽

pp. 681-684

Author(s):

Akira TANIZAKI ◽

Shiro MURAI ◽

Akira TAKASE ◽

Satoshi HOMBO

Keyword(s):

High Precision ◽

Precision Machining ◽

Machining Center

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Neural Networks-Genetic Algorithm Model for Modeling of Nonlinear Evaporation and Evapotranspiration Time Series 1. Theory and Application of the Model

Journal of Korea Water Resources Association ◽

10.3741/jkwra.2007.40.1.073 ◽

2007 ◽

Vol 40 (1) ◽

pp. 73-88 ◽

Author(s):

Sung-Won Kim ◽

Hung-Soo Kim

Keyword(s):

Genetic Algorithm ◽

Neural Networks ◽

Time Series ◽

Genetic Algorithm Model

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Lithium-ion battery state of health estimation using the incremental capacity and wavelet neural networks with genetic algorithm

Journal of Energy Storage ◽

10.1016/j.est.2021.102570 ◽

2021 ◽

Vol 38 ◽

pp. 102570

Author(s):

Chun Chang ◽

Qiyue Wang ◽

Jiuchun Jiang ◽

Tiezhou Wu

Keyword(s):

Genetic Algorithm ◽

Neural Networks ◽

Lithium Ion Battery ◽

Lithium Ion ◽

State Of Health ◽

Wavelet Neural Networks ◽

Incremental Capacity

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Simultaneous spectrophotometric quantitative analysis of velpatasvir and sofosbuvir in recently approved FDA pharmaceutical preparation using artificial neural networks and genetic algorithm artificial neural networks

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy ◽

10.1016/j.saa.2021.119465 ◽

2021 ◽

Vol 251 ◽

pp. 119465

Author(s):

Khalid A.M. Attia ◽

Nasr M. El-Abasawi ◽

Ahmed El-Olemy ◽

Ahmed H. Abdelazim ◽

Abdelrahman I. Goda ◽

...

Keyword(s):

Genetic Algorithm ◽

Neural Networks ◽

Artificial Neural Networks ◽

Quantitative Analysis ◽

Pharmaceutical Preparation ◽

Artificial Neural

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Automatic worst case pattern generation using neural networks & genetic algorithm for estimation of switching noise on power supply lines in CMOS circuits

The Eighth IEEE European Test Workshop, 2003. Proceedings. ◽

10.1109/etw.2003.1231676 ◽

2004 ◽

Author(s):

E. Liau ◽

D. Schmitt-Landsiedel

Keyword(s):

Genetic Algorithm ◽

Neural Networks ◽

Power Supply ◽

Pattern Generation ◽

Cmos Circuits ◽

Switching Noise ◽

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Hybrid back-propagation/genetic algorithm for multilayer feedforward neural networks

WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000 ◽

10.1109/icosp.2000.894556 ◽

2002 ◽

Author(s):

Chun Lu ◽

Bingxue Shi

Keyword(s):

Genetic Algorithm ◽

Neural Networks ◽

Back Propagation ◽

Feedforward Neural Networks

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Nonlinear Time-Series Analysis of Pulsation of Post-AGB Stars by Genetic Algorithm/Neural Network Hybrid Systems

International Astronomical Union Colloquium ◽

10.1017/s0252921100057419 ◽

2000 ◽

Vol 176 ◽

pp. 135-136

Author(s):

Toshiki Aikawa

Keyword(s):

Neural Network ◽

Genetic Algorithm ◽

Neural Networks ◽

Time Series ◽

Artificial Neural Networks ◽

Hybrid System ◽

Nonlinear Time Series ◽

Photometric Data ◽

Nonlinear Time Series Analysis ◽

AbstractSome pulsating post-AGB stars have been observed with an Automatic Photometry Telescope (APT) and a considerable amount of precise photometric data has been accumulated for these stars. The datasets, however, are still sparse, and this is a problem for applying nonlinear time series: for instance, modeling of attractors by the artificial neural networks (NN) to the datasets. We propose the optimization of data interpolations with the genetic algorithm (GA) and the hybrid system combined with NN. We apply this system to the Mackey–Glass equation, and attempt an analysis of the photometric data of post-AGB variables.

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