Results 41 to 50 of about 1,432,311 (298)
Pareto Based Performance Framework for Urban Greening: Visualizing Trade offs between Cost, Carbon Sequestration, and Shading [PDF]
E3S Web of ConferencesUrban greening in construction planning often entails trade offs between cost and ecological performance. This study develops a multi-objective optimization framework that explicitly exposes and interprets the trade-offs among cost, carbon sequestration,
Lin Yu-Cian, Chan Ying-Chieh
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Advanced Engineering Materials, EarlyView.We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
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Operations Research PerspectivesThis paper proposes a novel method of Pareto front generation from a set of piecewise linear trade-off curves typically encountered in bi-objective just-in-time (JIT) scheduling problems. We have considered the simultaneous minimization of total weighted
Sona Babu, B.S. Girish
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From a Pareto Front to Pareto Regions: A Novel Standpoint for Multiobjective Optimization
Mathematics, 2021 This work presents a novel approach for multiobjective optimization problems, extending the concept of a Pareto front to a new idea of the Pareto region.
Carine M. Rebello +6 more
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New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design
Advanced Engineering Materials, EarlyView.This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare +5 more
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Learning and Selection of Pareto Optimal Policies Matching User Preferences
IEEE AccessReinforcement learning, which is attracting attention as a method for optimizing sequential decision-making, primarily focuses on scenarios with a single objective.
Akinori Tamura, Sachiyo Arai
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Advanced Functional Materials, EarlyView.HfxZr1−xO2${\rm Hf}_x{\rm Zr}_{1-x}{\rm O}_2$ offers CMOS‐compatible nanoscale ferroelectricity yet suffers from a high Ec${\rm E}_c$ demanding large operating voltages. A unified phase‐field framework spanning AFE/FE/DE phases shows how FE grains soften neighboring AFE grains over λ$\lambda$ ≈$\approx$ 22–37 nm.
P. Pankaj +4 more
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Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2017 10 pages, accepted at GECCO'17 as a poster paper (2 pages)
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Advanced Functional Materials, EarlyView.Autonomous scanning probe microscopy and multi‐objective Bayesian optimization navigate a ternary (Al,Sc,B)N combinatorial library. Registered photoluminescence, electron‐probe compositional mapping, and X‐ray diffraction connect local electromechanical function to defect‐sensitive emission, composition, and crystal structure.
Yu Liu +12 more
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Multi-Objective Feature Selection Method Based on Hybrid MI and PSO Algorithm
Jisuanji kexue yu tansuo, 2020 Feature selection is an important pre-processing in data mining, due to a lot of redundant and irrelevant features in datasets. A filter-wrapper multi-objective feature selection method based on hybrid mutual information and particle swarm optimization ...
WANG Jinjie, LI Wei
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