Results 61 to 70 of about 14,697 (286)

Pareto-front shape in multiobservable quantum control

, 2017
Many scenarios in the sciences and engineering require simultaneous optimization of multiple objective functions, which are usually conflicting or competing.
Re-Bing Wu, Qiuyang Sun, Sun, Qiuyang, Rabitz, Herschel, Wu, Re-Bing, Herschel Rabitz   +5 more
core   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

Advanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu, Longfei Lv, Fan Zhang, Si Zhou, Weiwei Gao, Jijun Zhao   +5 more
wiley   +1 more source

Beyond the Pareto Front: Utilizing the Entire Population for Decision-Making in Evolutionary Machine Learning

Mathematics
Decision-making plays a pivotal role in data-driven optimization, aiming to achieve optimal results by identifying the most effective combination of input variables.
Parastoo Dehnad, Azam Asilian Bidgoli, Shahryar Rahnamayan   +2 more
doaj   +1 more source

Pareto-optimal cycles for power, efficiency and fluctuations of quantum heat engines using reinforcement learning

Physical Review Research, 2023
The full optimization of a quantum heat engine requires operating at high power, high efficiency, and high stability (i.e., low power fluctuations).
Paolo A. Erdman, Alberto Rolandi, Paolo Abiuso, Martí Perarnau-Llobet, Frank Noé   +4 more
doaj   +1 more source

Pareto Front Approximation Using a Hybrid Approach

, 2013
A new method is proposed for approximating a Pareto front of a bound constrained biobjective optimization problem (BOP) where the evaluation of the objective functions is very expensive and/or the structure of the objective functions either cannot be ...
Deshpande, Shubhangi, Canfield, Robert A., Watson, Layne T.   +2 more
core   +1 more source

Pareto front of the sparse NMF.

, 2023
The α = 0.4 and β = 0.4 parameters are selected to incorporate a fair number of members to the Pareto front, and also have most of the objectives incorporated into a component.
János Abonyi (10106040), Ádám Ipkovich (15285785), Gyula Dörgő (13919393), Károly Héberger (390762)   +3 more
core   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source

Time–cost–quality tradeoff Pareto front using MOIWCA.

, 2023
Time–cost–quality tradeoff Pareto front using MOIWCA.
Xuemei Li (232384), Guanyi Liu (10099336), Khalid Mehmood Alam (14593291)   +2 more
core   +1 more source

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

Advanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei, Yong Li, Chenchong Wang, Lingyu Wang, Xiang Song, Keming Mao, Yu Zhang, Wei Xu   +7 more
wiley   +1 more source

Comparison of evolutionary multi objective optimization algorithms in optimum design of water distribution network

Ain Shams Engineering Journal, 2019
In this paper, the application of three well-known multi-objective optimization algorithms to water distribution network (WDN) optimum design has been considered.
H. Monsef, M. Naghashzadegan, A. Jamali, R. Farmani   +3 more
doaj   +1 more source