Matches in SemOpenAlex for { <https://semopenalex.org/work/W6851639> ?p ?o ?g. }
Showing items 1 to 61 of
61
with 100 items per page.
- W6851639 abstract "The quantity of data available to scientists in all disciplines is increasing at an exponential rate, yet the insight necessary to distill data into scientific knowledge must still be supplied by human experts. This widening gap between data and insight can be bridged with data-driven modeling, in which computational methods shift much of the work in creating models from humans to computers. Traditional approaches to data-driven modeling require that the form of the model be fixed in advance, which requires substantial human effort and limits the complexity of problems that can be addressed. In contrast, a newer approach to automated modeling based on evolutionary computation (EC) removes such restrictions on the form of models. This free-form modeling has the potential both to reduce human effort for routine modeling and to make complex problems more tractable. Although major advances in EC-based modeling have been made in recent years, many challenges remain. These challenges include three features often seen in biological systems: complex nonlinear behavior, multiple time scales, and hidden variables. This work addresses these challenges by developing new approaches to EC-based modeling, with applications to neuroscience, systems biology, ecology, and other fields. The contributions of this work consist of three primary lines of research. In the first line of research, EC-based methods for the automated design of analog electrical circuits are adapted for the modeling of electrical systems studied in neurophysiology that display complex, nonlinear behavior, such as ion channels. In the second line of research, EC-based methods for symbolic modeling are extended to facilitate the modeling of dynamical systems with multiple time scales, such as those found throughout ecology and other fields. Finally, in the third line of research, established EC-based algorithms are extended with the capability to model dynamical systems as systems of differential equations with hidden variables, which can contribute in an essential way to the observed dynamics of a physical system yet historically have presented a particularly difficult challenge to automated modeling." @default.
- W6851639 created "2016-06-24" @default.
- W6851639 creator A5025894735 @default.
- W6851639 creator A5078661757 @default.
- W6851639 date "2014-01-01" @default.
- W6851639 modified "2023-09-26" @default.
- W6851639 title "Data-driven, free-form modeling of biological systems" @default.
- W6851639 hasPublicationYear "2014" @default.
- W6851639 type Work @default.
- W6851639 sameAs 6851639 @default.
- W6851639 citedByCount "0" @default.
- W6851639 crossrefType "dissertation" @default.
- W6851639 hasAuthorship W6851639A5025894735 @default.
- W6851639 hasAuthorship W6851639A5078661757 @default.
- W6851639 hasConcept C111472728 @default.
- W6851639 hasConcept C127413603 @default.
- W6851639 hasConcept C138379479 @default.
- W6851639 hasConcept C138885662 @default.
- W6851639 hasConcept C154945302 @default.
- W6851639 hasConcept C167343916 @default.
- W6851639 hasConcept C2522767166 @default.
- W6851639 hasConcept C41008148 @default.
- W6851639 hasConcept C44154836 @default.
- W6851639 hasConcept C539667460 @default.
- W6851639 hasConceptScore W6851639C111472728 @default.
- W6851639 hasConceptScore W6851639C127413603 @default.
- W6851639 hasConceptScore W6851639C138379479 @default.
- W6851639 hasConceptScore W6851639C138885662 @default.
- W6851639 hasConceptScore W6851639C154945302 @default.
- W6851639 hasConceptScore W6851639C167343916 @default.
- W6851639 hasConceptScore W6851639C2522767166 @default.
- W6851639 hasConceptScore W6851639C41008148 @default.
- W6851639 hasConceptScore W6851639C44154836 @default.
- W6851639 hasConceptScore W6851639C539667460 @default.
- W6851639 hasLocation W68516391 @default.
- W6851639 hasOpenAccess W6851639 @default.
- W6851639 hasPrimaryLocation W68516391 @default.
- W6851639 hasRelatedWork W149709897 @default.
- W6851639 hasRelatedWork W1558923554 @default.
- W6851639 hasRelatedWork W159015046 @default.
- W6851639 hasRelatedWork W1964611497 @default.
- W6851639 hasRelatedWork W2019227129 @default.
- W6851639 hasRelatedWork W2484718471 @default.
- W6851639 hasRelatedWork W2496984222 @default.
- W6851639 hasRelatedWork W2542731556 @default.
- W6851639 hasRelatedWork W2807384483 @default.
- W6851639 hasRelatedWork W2855547807 @default.
- W6851639 hasRelatedWork W2892765915 @default.
- W6851639 hasRelatedWork W2893374481 @default.
- W6851639 hasRelatedWork W2902656906 @default.
- W6851639 hasRelatedWork W2980019978 @default.
- W6851639 hasRelatedWork W3046778803 @default.
- W6851639 hasRelatedWork W3136769306 @default.
- W6851639 hasRelatedWork W3207522883 @default.
- W6851639 hasRelatedWork W69288136 @default.
- W6851639 hasRelatedWork W69872152 @default.
- W6851639 hasRelatedWork W89610872 @default.
- W6851639 isParatext "false" @default.
- W6851639 isRetracted "false" @default.
- W6851639 magId "6851639" @default.
- W6851639 workType "dissertation" @default.