Results 41 to 50 of about 50,616 (261)
Airborne LIDAR-Derived Aboveground Biomass Estimates Using a Hierarchical Bayesian Approach
Remote Sensing, 2019 Conventional ground survey data are very accurate, but expensive. Airborne lidar data can reduce the costs and effort required to conduct large-scale forest surveys. It is critical to improve biomass estimation and evaluate carbon stock when we use lidar
Mengxi Wang +4 more
doaj +1 more source
Alexandria Engineering Journal, 2023 The hierarchical models have not only a major concern with developing computational schemes but also assist in inferring the multi-parameter problems.
Azeem Iqbal +2 more
doaj +1 more source
HIERARCHICAL BAYESIAN MODELLING OF A FAMILY OF FRFS
Proceedings of the 14th International Workshop on Structural Health Monitoring, 2023 Population-based structural health monitoring (PBSHM) aims to share valuable information among members of a population, such as normal- and damage-condition data, to improve inferences regarding the health states of the members. Even when the population is comprised of nominally-identical structures, benign variations among the members will exist as a ...
Dardeno, T.A. +4 more
openaire +2 more sources
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +2 more
wiley +1 more source
Frontiers in Marine Science, 2016 We present a Hierarchical Bayesian version of Pollock's Closed Robust Design for studying the survival, temporary-migration, and abundance of marked animals.
Robert William Rankin +5 more
doaj +1 more source
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
A normative model for Bayesian combination of subjective probability estimates
Judgment and Decision Making, 2023 Combining experts’ subjective probability estimates is a fundamental task with broad applicability in domains ranging from finance to public health. However, it is still an open question how to combine such estimates optimally.
Susanne Trick +2 more
doaj +1 more source
A hierarchical Bayesian model for syntactic priming [PDF]
CoRR6 pages; accepted to CogSci ...
Xu, Weijie, Futrell, Richard
openaire +3 more sources
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
wiley +1 more source
Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying
Advanced Engineering Materials, EarlyView.An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara +8 more
wiley +1 more source