Results 61 to 70 of about 94,222 (207)
Considering spatiotemporal evolutionary information in dynamic multi‐objective optimisation
Abstract Preserving population diversity and providing knowledge, which are two core tasks in the dynamic multi‐objective optimisation (DMO), are challenging since the sampling space is time‐ and space‐varying. Therefore, the spatiotemporal property of evolutionary information needs to be considered in the DMO.
Qinqin Fan +3 more
wiley +1 more source
Invariant Measure and Universality of the 2D Yang–Mills Langevin Dynamic
ABSTRACT We prove that the Yang–Mills (YM) measure for the trivial principal bundle over the two‐dimensional torus, with any connected, compact structure group, is invariant for the associated renormalised Langevin dynamic. Our argument relies on a combination of regularity structures, lattice gauge‐fixing and Bourgain's method for invariant measures ...
Ilya Chevyrev, Hao Shen
wiley +1 more source
ABSTRACT The leading‐order asymptotic behavior of the solution of the Cauchy initial‐value problem for the Benjamin–Ono equation in L2(R)$L^2(\mathbb {R})$ is obtained explicitly for generic rational initial data u0$u_0$. An explicit asymptotic wave profile uZD(t,x;ε)$u^\mathrm{ZD}(t,x;\epsilon)$ is given, in terms of the branches of the multivalued ...
Elliot Blackstone +3 more
wiley +1 more source
This study investigates ground subsidence during tunnel excavation in karst areas, highlighting the combined effects of karst cave proximity, cave size, and soil spatial variability. Findings suggest that shorter cave distances and larger cave sizes increase subsidence variability, and a modified Peck formula is proposed for more accurate subsidence ...
Zhenghong Su +4 more
wiley +1 more source
Thalamic connectivity mirrors spatial maps of network dysfunction in nonlesional focal epilepsy
Abstract Objective Focal epilepsy is increasingly conceptualized as a network disorder, yet the extent to which network dysfunction reflects a shared phenotype remains unknown. Spatially conserved patterns of network dysfunction may implicate a centralized mechanism underlying widespread impairment.
Joline M. Fan +7 more
wiley +1 more source
Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices
ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer +3 more
wiley +1 more source
Quadratic Hedging of American Options Under GARCH Models
ABSTRACT American options are widely traded in financial markets, yet there is a scarcity of literature on hedging in incomplete markets. In this paper, we derive optimal hedging ratios and option values using Local Risk Minimization (LRM) and Global Risk Minimization (GRM) hedging strategies through dynamic programming.
Junmei Ma, Chen Wang, Wei Xu
wiley +1 more source
How (not) to Cage an Electron: The Perfluoro Cage Effect as an Extrinsic Molecular Property
A rigorous definition within Kohn–Sham density functional theory is presented for the notion of an caged electron inside perfluorinated fullerenes as radical anions. ABSTRACT The notion of a (molecular) electron cage was coined for the unique hosting capacity of perfluorocubane, suggesting the “encapsulation of an electron” within the highly symmetric ...
Andreas Riedmiller +2 more
wiley +1 more source
Abstract Background Attention‐deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition with significant cognitive and social impacts. Identifying reliable biomarkers for ADHD is crucial for developing personalised therapies. Electroencephalography (EEG) alpha oscillations (8–12 Hz) have been suggested as a potential biomarker, but ...
Julio Rodriguez‐Larios +2 more
wiley +1 more source
Elevator dynamic monitoring and early warning system based on machine learning algorithm
In order to monitor and warn the elevator dynamics, in this work, the machine learning algorithm is introduced, and the particle swarm algorithm is used to perfect the model. The model is optimised, and the experimental comparison shows that the optimisation of the model parameters can further improve the accuracy of the elevator load prediction. Then,
Shuai Zhang, Qiangguo Yin, Jinlong Wang
wiley +1 more source

