Results 51 to 60 of about 2,364,396 (151)

Greedy permanent magnet optimization

Nuclear Fusion, 2023
A number of scientific fields rely on placing permanent magnets in order to produce a desired magnetic field. We have shown in recent work that the placement process can be formulated as sparse regression.
Alan A. Kaptanoglu, Rory Conlin, Matt Landreman   +2 more
doaj   +1 more source

Quadratic versus Polynomial Unconstrained Binary Models for Quantum Optimization illustrated on Railway Timetabling

Quantum Approximate Optimization Algorithm (QAOA) is one of the most short-term promising quantum-classical algorithm to solve unconstrained combinatorial optimization problems.
Lavignac, Marion, Bourreau, Eric, Grange, Camille, Pozzoli, Valentina   +3 more
core   +5 more sources

Lasso for hierarchical polynomial models

Canadian Journal of Statistics, EarlyView.
Abstract The divisibility conditions implicit in a polynomial hierarchy suggest parameter constraints in regression. With this idea, we establish strong and weak hierarchies for both the lasso and relaxed lasso. Our proposal extends prior work on hierarchical lasso, which was mainly concerned with models of degree 2.
H. Maruri‐Aguilar, S. Lunagómez
wiley   +1 more source

Quantifying Actin Persistence Length in S. pombe and S. cerevisiae: The Impact of Data Size, Filament Length and Fitting Strategy

Cytoskeleton, EarlyView.
ABSTRACT Actin filaments exhibit isoform and species‐specific mechanical properties that are commonly quantified via their persistence length, yet the reliability of such measurements depends not only on the analysis method but also on dataset characteristics.
Peter Nietmann, Andrejus Suchenko, Andreas Janshoff, Mohan K. Balasubramanian   +3 more
wiley   +1 more source

Analytical Approximation-Based Approach for Passenger Flow Control Strategy in Oversaturated Urban Rail Transit Systems

Journal of Advanced Transportation, 2023
Focusing on a heavily congested urban rail corridor, this study investigates the passenger flow control strategy optimization problem from a mesoscopic perspective to reduce platform congestion and enhance service quality. Based on a quadratic functional
Qian Zhu, Xiaoning Zhu, Pan Shang, Lingyun Meng   +3 more
doaj   +1 more source

Corporate Social Responsibility and Corporate Tax Avoidance in Europe: Evidence From the Anti‐Tax Avoidance Directives

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT This study examines the relationship between corporate social responsibility (CSR) and corporate tax avoidance (CTA) in the European Union, exploiting institutional variation arising from CSR disclosure regimes and the introduction of the Anti‐Tax Avoidance Directives (ATAD).
Alessandro Migliavacca
wiley   +1 more source

An Efficient Subspace Minimization Conjugate Gradient Method for Solving Nonlinear Monotone Equations with Convex Constraints

Axioms
The subspace minimization conjugate gradient (SMCG) methods proposed by Yuan and Store are efficient iterative methods for unconstrained optimization, where the search directions are generated by minimizing the quadratic approximate models of the ...
Taiyong Song, Zexian Liu
doaj   +1 more source

A Genetic Algorithm‐Optimized LSTM Framework for Mechanics‐Conditioned Reconstruction of Stress–Strain Curves in High‐Performance Cementitious Materials

Energy Science &Engineering, EarlyView.
GA‐optimized LSTM for full stress–strain curve prediction of high‐performance cementitious materials. Compression‐test data are preprocessed (cleaning, normalization, interpolation/standardization, and Savitzky–Golay smoothing). A Genetic Algorithm tunes LSTM hyperparameters, while a physics‐informed loss enforces stiffness, peak response ( σ max ...
Mahmoud AlJamal, Qasim Aljamal, Mohammad Q. Al‐Jamal, Bashar S. Khassawneh, Ayoub Alsarhan, Dimah Al‐Fraihat, Abdulmohsen Algarni, Osama Harfoushi   +7 more
wiley   +1 more source

Immunizing Conic Quadratic Optimization Problems Against Implementation Errors [PDF]

We show that the robust counterpart of a convex quadratic constraint with ellipsoidal implementation error is equivalent to a system of conic quadratic constraints.
Ben-Tal, A., Hertog, D. den
core  

A Large-Scale Quadratic Unconstrained Binary Optimization using Photonic Quantum Microprocessor

A large-scale Quadratic Unconstrained Binary Optimization with 81 and 369 vertices is studied using a photonic quantum microprocessor. Through nested iteration and parallel optimization, it achieves approximation rates of 99.59% and 97.24%, respectively.
Hao Yu, Menglong Fang, Hong Cai, Daiqin Su, Ai-Qun Liu, Zan Tang, Wei Wang, Xiang Wu, Yuxiang Li   +8 more
core   +1 more source