Results 91 to 100 of about 47,340 (341)
Delta-Nabla Optimal Control Problems
, 2010 We present a unified treatment to control problems on an arbitrary time scale by introducing the study of forward-backward optimal control problems. Necessary optimality conditions for delta-nabla isoperimetric problems are proved, and previous results ...
Agnieszka B Malinowska +7 more
core +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
Advanced Intelligent Discovery, EarlyView.This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
Trade-off drives Pareto optimality of within- and among-year emergence timing in response to increasing aridity. [PDF]
Evol Appl, 2021 Waterton J +3 more
europepmc +1 more source
Pareto-Optimality in Linear Regression
Journal of Mathematical Analysis and Applications, 1995 In this paper the linear regression problem is studied in the context of vector optimization theory. The set of Pareto-optimal solutions is represented as the set of optimal solutions to certain optimization problems, and is geometrically characterized as a finite union of bounded polyhedra.
Carrizosa Priego, Emilio José +4 more
openaire +3 more sources
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Angewandte Chemie, EarlyView.Pareto optimal compositions of alloy catalyst for oxygen reduction reaction are uncovered through multi‐objective Bayesian optimization of activity, stability, and material cost in an eight‐element high‐entropy alloy composition space. The substantial Pareto front obtained is compared to experimental literature and analyzed to elucidate the roles and ...
Mads K. Plenge +4 more
wiley +2 more sources
Equal probability for the best and the assignment of identical indivisible objects [PDF]
We consider the problem of allocating several units of an indivisible object among agents with single-peaked utility functions. We introduce an axiom called equal probability for the best, and show that it is equivalent to both equal treatment of equals ...
Hideki MIZUKAMI, Wataru KUREISHI
core
Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
The 80/20 Principle: to use or not to use
RUDN Journal of Economics, 2010 The phenomenon of discovery and usage of Pareto principle phenomenon is considered. Areas of application of this principle (time-management, ABC-analysis, assortment organizing, Pareto-analysis of optimality) is described.
A P Pakhomov
doaj