Results 61 to 70 of about 21,806 (260)
Advanced Intelligent Discovery, EarlyView.This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu +5 more
wiley +1 more source
Multiobjective Optimization Method for Energy-Saving Design of Green Buildings
Advances in Civil EngineeringA multiobjective optimization model for energy-saving design of green buildings is established by considering the two key indicators (energy efficiency and comfort) that are important for the design of green buildings.
Yuanting Yang, Fengxiang Lu, Lan Qing
doaj +1 more source
Complexity, 2018 In association with the development of intermittent renewable energy generation (REG), dynamic multiobjective dispatch faces more challenges for power system operation due to significant REG uncertainty.
Tingli Cheng +6 more
doaj +1 more source
Parameter influence law analysis and optimal design of a dual mass flywheel
International Journal of Mechanical System Dynamics, 2022 The influence of the dynamic parameters of a dual mass flywheel (DMF) on its vibration reduction performance is analyzed, and several optimization algorithms are used to carry out multiobjective DMF optimization design.
Guangqiang Wu, Guoqiang Zhao
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Advanced Intelligent Discovery, EarlyView.A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley +1 more source
Numerical results for the multiobjective trust region algorithm MHT
Data in Brief, 2019 In this data article, we report data and numerical results related to the research article entitled ”A trust region algorithm for heterogeneous multiobjective optimization” by Thomann and Eichfelder in SIAM Journal on Optimization.
Jana Thomann, Gabriele Eichfelder
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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
Computing the set of Epsilon-efficient solutions in multiobjective space mission design [PDF]
, 2011 In this work, we consider multiobjective space mission design problems. We will start from the need, from a practical point of view, to consider in addition to the (Pareto) optimal solutions also nearly optimal ones.
Vasile, Massimiliano +2 more
core +1 more source
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
Reliability-based multiobjective optimization using the satisficing trade-off method
Mechanical Engineering Journal, 2014 This study proposes a reliability-based multiobjective optimization (RBMO) approach using the satisficing trade-off method (STOM). STOM is a multiobjective optimization method that obtains a highly accurate single Pareto solution, regardless of the shape
Nozomu KOGISO +2 more
doaj +1 more source