Results 201 to 210 of about 998,636 (282)

Bieten KI‐basierte Surrogatmodelle einen Mehrwert für die Prozessoptimierung? — Untersuchungen zu praktischen Anwendungsbeispielen im C4‐Verbund Can AI‐based surrogate models offer added value for process optimization? — Investigations into practical application examples in the C4‐Verbund

Chemie Ingenieur Technik, EarlyView.
KI‐basierte Surrogatmodelle ermöglichen die Echtzeitoptimierung chemischer Prozesse durch die präzise Abbildung komplexer Zusammenhänge bei reduzierter Rechenzeit. Anhand zweier industrieller Anwendungsfälle aus der C4‐Chemie wird das Potenzial modellbasierter Optimierung systematisch demonstriert.
Bastian Bruns, Maximilian Wessner, Doris Birkefeld, Niklas Paul, Robert Franke   +4 more
wiley   +1 more source

Comparative Network Reconstruction using mixed integer programming. [PDF]

Bioinformatics, 2018
Bosdriesz E, Prahallad A, Klinger B, Sieber A, Bosma A, Bernards R, Blüthgen N, Wessels LFA.   +7 more
europepmc   +1 more source

A Graph‐Based Generative Artificial Intelligence Methodology for Autocorrection of Utility‐System P&IDs

Chemie Ingenieur Technik, EarlyView.
This work explores generative AI for automated revision of Piping and Instrumentation Diagrams (P&IDs). We frame P&ID correction as a translation problem, converting attributed P&ID graphs into sequences and learning revisions with a transformer‐based model.
Lukas Schulze Balhorn, Dominik P. Goldstein, Niels Seijsener, Kevin Dao, Ge H. M. Driessen, Artur M. Schweidtmann   +5 more
wiley   +1 more source

Identifying A- and P-site locations on ribosome-protected mRNA fragments using Integer Programming. [PDF]

Sci Rep, 2019
Ahmed N, Sormanni P, Ciryam P, Vendruscolo M, Dobson CM, O'Brien EP.   +5 more
europepmc   +1 more source

Dynamic survival risk prediction with time‐varying high‐dimensional images

Canadian Journal of Statistics, EarlyView.
Abstract Integrating longitudinal data with survival models is a prevalent strategy for dynamic survival risk prediction while accounting for subjects' longitudinally observed variables. However, existing methods primarily focus on scalar longitudinal data and seldom tackle the complexities associated with high‐dimensional longitudinal imaging data ...
Bingfan Liu, Haolun Shi, Shu Jiang, Liangliang Wang, Da Ma, Mirza Faisal Beg, Jiguo Cao, for the Alzheimer's Disease Neuroimaging Initiative   +7 more
wiley   +1 more source

Copula‐based joint modelling of emergency department visits with time‐varying dependence

Canadian Journal of Statistics, EarlyView.
Abstract Jointly modelling multiple correlated count time series is essential in health services research, where outcomes like emergency visits for mental health and substance use often evolve together. Ignoring these dependencies can obscure meaningful trends and limit the effectiveness of policy evaluation.
Guanjie Lyu, Cindy Feng, Lihui Liu
wiley   +1 more source

Bi-objective integer programming for RNA secondary structure prediction with pseudoknots. [PDF]

BMC Bioinformatics, 2018
Legendre A, Angel E, Tahi F.
europepmc   +1 more source

Analyzing zero‐truncated recurrent event data by stratified regression with time‐varying coefficients

Canadian Journal of Statistics, EarlyView.
Abstract This article presents a strategy for conducting regression analysis of zero‐truncated recurrent event data. The research is partly motivated by a pediatric mental health care (PMHC) program based on administrative data. We are particularly interested in how the occurrence of an event depends on its past occurrences and the associated ...
Anqi A. Chen, X. Joan Hu, Rhonda J. Rosychuk, Leilei Zeng   +3 more
wiley   +1 more source

An integer programming framework for inferring disease complexes from network data. [PDF]

Bioinformatics, 2016
Mazza A, Klockmeier K, Wanker E, Sharan R.   +3 more
europepmc   +2 more sources

Stochastic integer programming for multi-disciplinary outpatient clinic planning. [PDF]

Health Care Manag Sci, 2019
Leeftink AG, Vliegen IMH, Hans EW.
europepmc   +1 more source