Results 1 to 10 of about 2,854,398 (286)
Knowledge-Guided Symbolic Regression for Interpretable Camera Calibration [PDF]
Journal of 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 ...
Rui Pimentel de Figueiredo
doaj +2 more sources
Application of the symbolic regression program AI-Feynman to psychology [PDF]
Frontiers in Artificial Intelligence, 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.
Masato Miyazaki +5 more
doaj +2 more sources
Learning interpretable network dynamics via universal neural symbolic regression [PDF]
Nature CommunicationsDiscovering 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 ...
Jiao Hu, Jiaxu Cui, Bo Yang
doaj +2 more sources
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
IET Collaborative Intelligent Manufacturing, 2021 Predictive models are increasingly deployed within smart manufacturing for the control of industrial plants. With this arises, the need for long‐term monitoring of model performance and adaptation of models if surrounding conditions change and the ...
Florian Bachinger +2 more
doaj +1 more source
Regression Models for Symbolic Interval-Valued Variables
Entropy, 2021 This paper presents new approaches to fit regression models for symbolic internal-valued variables, which are shown to improve and extend the center method suggested by Billard and Diday and the center and range method proposed by Lima-Neto, E.A.and De ...
Jose Emmanuel Chacón +1 more
doaj +1 more source
Symbolic Regression Methods for Reinforcement Learning
IEEE Access, 2021 Reinforcement learning algorithms can solve dynamic decision-making and optimal control problems. With continuous-valued state and input variables, reinforcement learning algorithms must rely on function approximators to represent the value function and ...
Jiri Kubalik +3 more
doaj +1 more source