Results 121 to 130 of about 13,618 (231)

Deep Embedding Koopman Neural Operator-Based Nonlinear Flight Training Trajectory Prediction Approach

Mathematics
Accurate flight training trajectory prediction is a key task in automatic flight maneuver evaluation and flight operations quality assurance (FOQA), which is crucial for pilot training and aviation safety management. The task is extremely challenging due
Jing Lu, Jingjun Jiang, Yidan Bai
doaj   +1 more source

Tensor network approximation of Koopman operators

We propose a tensor network framework for approximating the evolution of observables of measure-preserving ergodic systems. Our approach is based on a spectrally-convergent approximation of the skew-adjoint Koopman generator by a diagonalizable, skew-adjoint operator $W_τ$ that acts on a reproducing kernel Hilbert space $\mathcal H_τ$ with coalgebra ...
Giannakis, Dimitrios, Jebelli, Mohammad Javad Latifi, Montgomery, Michael, Pfeffer, Philipp, Schumacher, Jörg, Slawinska, Joanna   +5 more
openaire   +2 more sources

A Meta‐Analytic Review of the Within‐Person Relationship Between Affect and Job Performance

Journal of Organizational Behavior, Volume 47, Issue 4, Page 685-709, May 2026.
ABSTRACT In recent years, there has been a shift from a between‐person, static view of trait affect and stable performance to a within‐person, dynamic view of state affect and episodic performance. However, these dynamic relationships have yet to be summarized.
John A. Aitken, Julia I. Baines, Madeline E. Wonders, Seth A. Kaplan, Jonathan E. Clark   +4 more
wiley   +1 more source

Learning Hamiltonian neural Koopman operator and simultaneously sustaining and discovering conservation laws

Physical Review Research
Accurately finding and predicting dynamics based on the observational data with noise perturbations is of paramount significance but still a major challenge presently.
Jingdong Zhang, Qunxi Zhu, Wei Lin
doaj   +1 more source

Deep Koopman Operator-based degradation modelling

Reliability Engineering & System Safety
With the current trend of increasing complexity of industrial systems, the construction and monitoring of health indicators becomes even more challenging. Given that health indicators are commonly employed to predict the end of life, a crucial criterion for reliable health indicators is their capability to discern a degradation trend. However, trending
Sergei Garmaev, Olga Fink
openaire   +2 more sources

Why Autonomous Vehicles Are Not Ready Yet: A Multi‐Disciplinary Review of Problems, Attempted Solutions, and Future Directions

Journal of Field Robotics, Volume 43, Issue 3, Page 2254-2341, May 2026.
ABSTRACT Personal autonomous vehicles can sense their surrounding environment, plan their route, and drive with little or no involvement of human drivers. Despite the latest technological advancements and the hopeful announcements made by leading entrepreneurs, to date no personal vehicle is approved for road circulation in a “fully” or “semi ...
Xingshuai Dong, Massimiliano Cappuccio, Fady Alnajjar, Luqman Ali, Hamad Al Jassmi, Essam Debie, Milad Ghasrikhouzani, Alessandro Lanteri, Tate McGregor, Oleksandra Molloy, Alice Plebe, Michael Regan, Eduardo Sandoval, Dongmo Zhang   +13 more
wiley   +1 more source

Deep Koopman operators for causal discovery

Communications Physics
Abstract Causal discovery aims to identify cause-effect mechanisms for better scientific understanding, explainable decision-making, and more accurate modeling. Standard statistical frameworks, such as Granger causality, lack the ability to quantify causal relationships in nonlinear dynamics due to the presence of complex feedback ...
Juan Nathaniel, Carla Roesch, Jatan Buch, Derek DeSantis, Adam Rupe, Kara D. Lamb, Pierre Gentine   +6 more
openaire   +1 more source

Modelling non‐linear psychological processes: Reviewing and evaluating non‐parametric approaches and their applicability to intensive longitudinal data

British Journal of Mathematical and Statistical Psychology, Volume 79, Issue 2, Page 263-293, May 2026.
Abstract Psychological concepts are increasingly understood as complex dynamic systems that change over time. To study these complex systems, researchers are increasingly gathering intensive longitudinal data (ILD), revealing non‐linear phenomena such as asymptotic growth, mean‐level switching, and regulatory oscillations.
Jan I. Failenschmid, Leonie V. D. E. Vogelsmeier, Joris Mulder, Joran Jongerling   +3 more
wiley   +1 more source

Frame Overlapping in Moral Markets: The Case of an ‘Open, Free, and Neutral’ Telecommunications Network

Journal of Management Studies, Volume 63, Issue 3, Page 1509-1537, May 2026.
Abstract This study explores how social movement activists, engaged in constructing and expanding moral markets, sustain the integrity of their initial moral values, avoiding dilution or cooptation by conventional market practices. Through a qualitative case study of a telecommunications network, we show that activists can expand a moral market by a ...
Daniel Arenas, Joan Rodón, Mireia Yter
wiley   +1 more source

Data-Driven Identification of Gas Turbine Engine Dynamics via Koopman Operator Genetic Algorithm

IEEE Access
Gas turbine engines (GTEs) are highly nonlinear control-nonaffine systems. Deriving their physics-based models can be challenging, particularly when some critical parameters can be difficult to measure or determine otherwise.
David Grasev
doaj   +1 more source