Bibliographic record
Abstract
In this special issue on Control and Optimization we present papers authored by a selected group of experts in these areas. The growing importance of control theory and optimization has been recognized in recent years. This is due not only to impressive theoretical developments, but also because of numerous applications to engineering, economics, life sciences, etc. This special issue is the tangible record of the special session on optimal control and its applications at AIMS 2016 Meeting which took place in Orlando, Florida, USA, on July 1 - July 5, 2016. Most of the papers collected here have been contributed by participants in the special session. Several invited speakers who were unable to attend the conference also contributed papers to this special issue. All submissions have been carefully refereed. The special issue contains fourteen papers contributed by well-known experts in control and optimization from Austria, Brazil, Canada, France, Germany, Israel, Italy, Japan, Portugal, Russia and USA. These papers cover a wide spectrum of important problems and topics of current research interest of control theory and optimization theory such as weak solutions of stochastic reaction diffusion equations, second order necessary and sufficient optimality conditions for singular solutions of partially-affine control problems, hybrid optimal control problems with semilinear parabolic equations, BV-extension of asymptotically constrained control-affine systems, optimal controls for an Ebola epidemic model, linear openness and feedback stabilization of nonlinear control systems, infinite-horizon multiobjective optimal control problems, partial differential equations in consumer theory, equilibrium locus of the flow on circular networks of cells, optimal control of non-autonomous SEIRS models, limit solutions in impulsive control, infinite horizon recursive variational problems in Banach spaces, algorithms for an optimal control problem with coupled hyperbolic and ordinary differential equation constraints and turnpike properties of approximate solutions of Bolza variational problems on large intervals. Therefore we feel that this special issue will be very valuable for many mathematicians and practitioners who are interested in recent developments in control theory and optimization as well as their numerous applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.467 | 0.313 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".