Artificial intelligence programming with LabVIEW:
genetic algorithms for instrumentation control and
optimization
J. Moore. Computer Methods and Programs in Biomedicine, 47 (1):
73--79(1995)
Abstract
A genetic algorithm for instrumentation control and
optimization was developed using the LabVIEW graphical
programming environment. The usefulness of this
methodology for the optimization of a closed loop
control instrument is demonstrated with minimal
complexity and the programming is presented in detail
to facilitate its adaptation to other LabVIEW
applications. Closed loop control instruments have
variety of applications in the biomedical sciences
including the regulation of physiological processes
such as blood pressure. The program presented here
should provide a useful starting point for those
wishing to incorporate genetic algorithm approaches to
LabVIEW mediated optimization of closed loop control
instruments.
NOT a GP. Fixed structure: 12 bit string. PMID:
7554864, UI: 96053901 Department of Human Genetics,
University of Michigan Medical School, Ann Arbor
48109-0618, USA.
%0 Journal Article
%1 moore:1995:LabVIEW
%A Moore, Jason H.
%D 1995
%J Computer Methods and Programs in Biomedicine
%K algorithms, artificial control, genetic graphical instrumentation intelligence, labview, languages, optimization programming
%N 1
%P 73--79
%T Artificial intelligence programming with LabVIEW:
genetic algorithms for instrumentation control and
optimization
%V 47
%X A genetic algorithm for instrumentation control and
optimization was developed using the LabVIEW graphical
programming environment. The usefulness of this
methodology for the optimization of a closed loop
control instrument is demonstrated with minimal
complexity and the programming is presented in detail
to facilitate its adaptation to other LabVIEW
applications. Closed loop control instruments have
variety of applications in the biomedical sciences
including the regulation of physiological processes
such as blood pressure. The program presented here
should provide a useful starting point for those
wishing to incorporate genetic algorithm approaches to
LabVIEW mediated optimization of closed loop control
instruments.
@article{moore:1995:LabVIEW,
abstract = {A genetic algorithm for instrumentation control and
optimization was developed using the LabVIEW graphical
programming environment. The usefulness of this
methodology for the optimization of a closed loop
control instrument is demonstrated with minimal
complexity and the programming is presented in detail
to facilitate its adaptation to other LabVIEW
applications. Closed loop control instruments have
variety of applications in the biomedical sciences
including the regulation of physiological processes
such as blood pressure. The program presented here
should provide a useful starting point for those
wishing to incorporate genetic algorithm approaches to
LabVIEW mediated optimization of closed loop control
instruments.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Moore, Jason H.},
biburl = {https://www.bibsonomy.org/bibtex/2527db2434f9428d065731d10fc00ea14/brazovayeye},
email = {jhm@superh.hg.med.umich.edu},
interhash = {8dc3655912f06356660dcc25dbbb4791},
intrahash = {527db2434f9428d065731d10fc00ea14},
journal = {Computer Methods and Programs in Biomedicine},
keywords = {algorithms, artificial control, genetic graphical instrumentation intelligence, labview, languages, optimization programming},
notes = {NOT a GP. Fixed structure: 12 bit string. PMID:
7554864, UI: 96053901 Department of Human Genetics,
University of Michigan Medical School, Ann Arbor
48109-0618, USA.},
number = 1,
pages = {73--79},
timestamp = {2008-06-19T17:47:34.000+0200},
title = {Artificial intelligence programming with {LabVIEW:}
genetic algorithms for instrumentation control and
optimization},
volume = 47,
year = 1995
}