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In this study, the mechanical performance of lightweight concrete exposed to high temperature has been modeled using genetic programming.
These include neuronal differentiation and, as a consequence, RETT syndrome, a disorder of the autism spectrum caused by mutation of methyl CpG binding protein MeCP2, which has been modeled using genetic engineered cells.
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In the present work VLE data of 3-Methylthiophene with various hydrocarbons were modeled using genetic algorithm.
The percentage of shear force carried by walls was modeled using genetic programming (GP) and Genetic Algorithm Artificial Neural Network (GAA) in rectangular channels with smooth and rough boundaries by Sheikh Khozani et al. (2016a, b).
For verification of operation, the proposed genetic algorithm was modeled using some aspects or parameters/genes and several simulations were run and results verified.
Ecologic niches and potential geographic distributions were modeled by using the Genetic Algorithm for Rule-set Prediction (GARP) (8 – 10 ).
Ecologic niches and potential geographic distributions were modeled by using the Genetic Algorithm for Rule-set Prediction (GARP) (30 – 32 ) (available from: URL: http://www.lifemapper.org/desktopgarp/).org/desktopgarp/
Currently, multiple FGFR3-related mouse models have been generated using genetic approach to study the role of FGFR3 in skeleton development and diseases.
The optimization model was solved using genetic algorithms in the MATLAB® platform coupled with the ASPEN Plus® software for process and thermodynamic modeling.
Non-linear estimation models were developed using genetic algorithm.
Linear QSAR models were developed using genetic function algorithm.
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