Hybrid Stochastic Genetic Evolution-Based Prediction Model of Received Input Voltage for Underground Imaging Applications
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{Baun:2023:ICBIR,
-
author = "Jonah Jahara Baun and Adrian Genevie Janairo and
Ronnie Concepcion and Kate Francisco and
Mike Louie Enriquez and R-Jay Relano and
Joseph Aristotle {de Leon} and Argel Bandala and Ryan Rhay Vicerra and
Jonathan Dungca",
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booktitle = "2023 8th International Conference on Business and
Industrial Research (ICBIR)",
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title = "Hybrid Stochastic Genetic Evolution-Based Prediction
Model of Received Input Voltage for Underground Imaging
Applications",
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year = "2023",
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pages = "549--555",
-
abstract = "The capacitive resistivity technique in underground
object detection comprises configured transmitter and
receiver antennas that are capacitively coupled to the
ground. However, underground imaging lacks a basis for
determining the received voltage for precise data
analysis. This study aimed to develop a prediction
model of the received input voltage signal amplitude
from the ground of a single-pair antenna underground
imaging system. The receiver antenna circuit for this
application is designed and simulated in Proteus
Software. Genetic Programming (GP) is applied to
predict the received input signal based on the shape of
the received waveform signal, operating frequency,
resistance of the waveform shaping circuit, and buffer
amplifier output signal. The resulting fitness function
of GP (4) is acceptable as it scored an R2 of
99.38percent with a negligible MSE of 0.0059 and an MAE
of 12.3423. Then, the GP fitness function is optimised
through Genetic Algorithm (GA), Differential Evolution
(DE), and Evolutionary Strategy (ES) in which the GP-GA
model outperformed the two hybrid models providing fast
convergence and 2.49e-8 best fitness value. This study
proved that GP can be effectively combined with
stochastic genetic evolution algorithms to avoid
lengthy mathematical calculations and accurately
estimate the natural voltage received from the
ground.",
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keywords = "genetic algorithms, genetic programming, Resistance,
Imaging, Stochastic processes, Receiving antennas,
Voltage, Predictive models, Conductivity, capacitive
resistivity technique, underground imaging, voltage
prediction, stochastic genetic evolution",
-
DOI = "doi:10.1109/ICBIR57571.2023.10147464",
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month = may,
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notes = "Also known as \cite{10147464}",
- }
Genetic Programming entries for
Jonah Jahara Garcia Baun
Adrian Genevie Galema Janairo
Ronnie S Concepcion II
Kate Francisco
Mike Louie Enriquez
R-Jay Relano
Joseph Aristotle R De Leon
Argel A Bandala
Ryan Rhay P Vicerra
Jonathan Dungca
Citations