Results 11 to 20 of about 13,019 (261)
Knowledge-Guided Symbolic Regression for Interpretable Camera Calibration. [PDF]
J ImagingCalibrating cameras accurately requires the identification of projection and distortion models that effectively account for lens-specific deviations. Conventional formulations, like the pinhole model or radial–tangential corrections, often struggle to ...
Pimentel de Figueiredo R.
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Application of the symbolic regression program AI-Feynman to psychology. [PDF]
Front Artif Intell, 2023 The discovery of hidden laws in data is the core challenge in many fields, from the natural sciences to the social sciences. However, this task has historically relied on human intuition and experience in many areas, including psychology.
Miyazaki M +5 more
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Glyph: Symbolic Regression Tools
Journal of Open Research Software, 2019 We present Glyph – a Python package for genetic programming based symbolic regression. Glyph is designed for usage in numerical simulations as well as real world experiments.
Markus Quade, Julien Gout, Markus Abel
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Learning interpretable network dynamics via universal neural symbolic regression. [PDF]
Nat CommunDiscovering governing equations of complex network dynamics is a fundamental challenge in contemporary science with rich data, which can uncover the hidden patterns and mechanisms of the formation and evolution of complex phenomena in various fields and ...
Hu J, Cui J, Yang B.
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Extending a physics-based constitutive model using genetic programming
Applications in Engineering Science, 2022 In material science, models are derived to predict emergent material properties (e.g. elasticity, strength, conductivity) and their relations to processing conditions.
Gabriel Kronberger +3 more
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Genetic Programming and Evolvable Machines, 2021 Modifying standard gradient boosting by replacing the embedded weak learner in favor of a strong(er) one, we present SyRBo: Symbolic-Regression Boosting. Experiments over 98 regression datasets show that by adding a small number of boosting stages -- between 2--5 -- to a symbolic regressor, statistically significant improvements can often be attained ...
Moshe Sipper, Jason H. Moore
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Application of symbolic regression for constitutive modeling of plastic deformation
Applications in Engineering Science, 2021 In numerical process simulations, in-depth knowledge about material behavior during processing in the form of trustworthy material models is crucial.
Evgeniya Kabliman +4 more
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Adaptive Chaotic Marine Predators Hill Climbing Algorithm for Large-Scale Design Optimizations
IEEE Access, 2023 Meta-heuristic algorithms have been effectively employed to tackle a wide range of optimisation issues, including structural engineering challenges.
Amin Abdollahi Dehkordi +3 more
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Priors for symbolic regression
Proceedings of the Companion Conference on Genetic and Evolutionary Computation, 2023 8+2 pages, 2 figures.
Bartlett, D, Desmond, H, Ferreira, P
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Prediction of microscopic residual stresses using genetic programming
Applications in Engineering Science, 2023 Metallurgical manufacturing processes commonly used in the industry (rolling, extrusion, shaping, machining, etc.) usually cause residual stress development which can remain after thermal heat treatments.
Laura Millán +7 more
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