Results 61 to 70 of about 2,015 (249)
An Improved Multi-Objective Artificial Bee Colony Optimization Algorithm with Regulation Operators
To achieve effective and accurate optimization for multi-objective optimization problems, a multi-objective artificial bee colony algorithm with regulation operators (RMOABC) inspired by the intelligent foraging behavior of honey bees was proposed in ...
Jiuyuan Huo, Liqun Liu
doaj +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
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
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
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
To overcome the premature-convergence of standard bat algorithm in solving the multi-objective optimal power flow (MOOPF) problems, a novel hybrid bat algorithm (NHBA) is proposed in this paper.
Gonggui Chen +3 more
doaj +1 more source
Optimization of an airfoil cooling system using a Pareto dominance approach [PDF]
The paper deals with the optimization of the airfoil internal cooling system in order to find the most efficient distribution of passages to reduce thermal stress and, at the same time, retain the temperature at a permissible level. Another objective is to carry out the task with as little coolant as possible.
openaire +2 more sources
An unexpected stochastic dominance: Pareto distributions, dependence, and diversification
We find the perhaps surprising inequality that the weighted average of independent and identically distributed Pareto random variables with infinite mean is larger than one such random variable in the sense of first-order stochastic dominance. This result holds for more general models including super-Pareto distributions, negative dependence, and ...
Chen, Yuyu, Embrechts, Paul, Wang, Ruodu
openaire +2 more sources
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Abstract Crop insurance is undoubtedly an extremely valuable element in protecting agricultural businesses, but in many cases standard indemnity‐based products have had very low uptake due to high transaction costs elevating premiums to unaffordable levels.
Amogh Prakasha Kumar +2 more
wiley +1 more source

