Results 201 to 210 of about 1,432,311 (298)

Pareto Front Sampling and Visualization

The tradeoff between different measures of fairness is captured by the so-called Pareto front, a visual representing the most one can achieve of a particular measure without sacrificing another. With many measures of production costs, machine learning inference quality, and fairness, the Pareto front is a high-dimensional object.
openaire   +1 more source

Groundwater Representation in Water Resource Planning: The Spatial and Temporal Sensitivity of Groundwater Supplies in England

Water and Environment Journal, EarlyView.
ABSTRACT Groundwater makes an important contribution to public water supplies, yet the dynamics of groundwater availability are often simplified in large‐scale water resource assessments. This study addresses that challenge on a national scale in England by integrating an empirically based groundwater supply model with a national‐scale water resource ...
Rachel Pugh, Anna Murgatroyd, Richard Rowan‐Robinson, Jim Hall   +3 more
wiley   +1 more source

Solving the 3D UAV Path Planning Problem Using an Improved Multi-Leader Multi-Objective Whale Optimization Algorithm. [PDF]

Biomimetics (Basel)
Tu B, Bao J, Zhou H, Huo Y, Han X, Hui N.   +5 more
europepmc   +1 more source

Multiple ortho‐mosaicking software pipelines produce comparable imagery‐derived wheat phenotypes

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Unmanned aerial systems (UAS) equipped with multispectral and RGB sensors offer valuable data for monitoring crop health and assessing disease severity. However, the wide range of available photogrammetric software complicates software selection for high‐throughput plant phenotyping.
Sanju Shrestha, Phillip D. Alderman, Grishma Ojha, Brett F. Carver   +3 more
wiley   +1 more source

Optimizing Sequential Decision Rules for Prostate Cancer Biopsy Management: A Multi-Objective Statistical Framework. [PDF]

J Am Stat Assoc
Qiu J, Zhao YQ, Wei J, Chinnaiyan AM, Tosoian J, Zheng Y.   +5 more
europepmc   +1 more source

Data-Driven Preference Sampling for Pareto Front Learning

Pareto front learning is a technique that introduces preference vectors in a neural network to approximate the Pareto front. Previous Pareto front learning methods have demonstrated high performance in approximating simple Pareto fronts.
Zhang, Jinyuan, Ye, Rongguang, Chen, Lei, Liao, Weiduo, Ishibuchi, Hisao   +4 more
core  

Accelerating Sustainable Epoxy Resin Development Through Bayesian Optimization and Inverse Design

Journal of Applied Polymer Science, Volume 143, Issue 37, October 5, 2026.
Development of a machine learning framework for the optimization of the Tg of partially bio‐based epoxy resin formulations in a 13‐component design space using Bayesian optimization, active learning, random design, and inverse design. The results show that the BO effectively navigates high‐dimensional formulation spaces, and the final ML model could ...
Natalie Wunder, Rodrigo Q. Albuquerque, Florian Max, Holger Ruckdäschel   +3 more
wiley   +1 more source

MPR-MOPSO-ASFS: A Stable Multi-Objective Feature Selection Algorithm for Metabolomics. [PDF]

Metabolites
Ye Q, Deng Z, Xie X, Huang Q, Luo J.
europepmc   +1 more source

Population balance modeling and digital design of degree of agglomeration in industrial crystallization

AIChE Journal, Volume 72, Issue 10, October 2026.
Abstract This study presents a coupled population balance model (PBM) for describing the degree‐of‐agglomeration (DoA) in crystallization by independently tracking total particle and agglomerate number densities. Applied to an industrial active pharmaceutical ingredient, the model outperformed bridge‐counting methods and accurately captured DoA trends ...
Yung‐Shun Kang, Hemalatha Kilari, Neda Nazemifard, C. Benjamin Renner, Yihui Yang, Charles Papageorgiou, Zoltan K. Nagy   +6 more
wiley   +1 more source