Results 51 to 60 of about 167,396 (260)
Markov Chain Monte Carlo Based Energy Use Behaviors Prediction of Office Occupants
Algorithms, 2020 Prediction of energy use behaviors is a necessary prerequisite for designing personalized and scalable energy efficiency programs. The energy use behaviors of office occupants are different from those of residential occupants and have not yet been ...
Qiao Yan +4 more
doaj +1 more source
Selecciones Matemáticas, 2023 The objective of the research is to estimate the transmission rate of an infection (β) in the SI epidemical model, using Bayesian statistical methods from observed data in Peru.
Emma Cambillo-Moyano +4 more
doaj +1 more source
Accelerating MCMC with active subspaces
, 2016 The Markov chain Monte Carlo (MCMC) method is the computational workhorse for Bayesian inverse problems. However, MCMC struggles in high-dimensional parameter spaces, since its iterates must sequentially explore the high-dimensional space.
Bui-Thanh, Tan +2 more
core +1 more source
������������������Logistic���������MCMC���������������������������������
, 2021 " Logistic MCMC "
openaire +1 more source
Advanced Intelligent Discovery, EarlyView.Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
American Journal of Botany, EarlyView.Abstract Premise Species of Deuterocohnia (17 spp.) show extraordinary variation in elevation (0–3900 m a.s.l.) and growth forms, and many have narrow geographic distributions in the west‐central Andes and the Peru‐Chile coast. Previous research using few plastid and nuclear loci failed to produce well‐resolved or supported phylogenies.
Bing Li +5 more
wiley +1 more source
Orthogonal MCMC algorithms [PDF]
2014 IEEE Workshop on Statistical Signal Processing (SSP), 2014 Monte Carlo (MC) methods are widely used in signal processing, machine learning and stochastic optimization. A well-known class of MC methods are Markov Chain Monte Carlo (MCMC) algorithms. In this work, we introduce a novel parallel interacting MCMC scheme, where the parallel chains share information using another MCMC technique working on the entire ...
Martino, Luca +4 more
openaire +3 more sources
The Anatomical Record, EarlyView.Abstract Dicynodonts (Anomodontia: Dicynodontia) were one of the main groups of terrestrial tetrapods in Permian and Triassic faunas. In Brazil, the genus Dinodontosaurus is one of the most common tetrapod taxon in the Triassic Santa Maria Supersequence. This genus has a complex taxonomic history and is represented in the Triassic of both Argentina and
Julia Lara Rodrigues de Souza +5 more
wiley +1 more source
International Journal of Assessment Tools in EducationThis research aims to compare the ability and item parameter estimations of Item Response Theory according to Maximum likelihood and Bayesian approaches in different Monte Carlo simulation conditions.
Ergül Demir, Eray Selçuk
doaj +1 more source
Regional Shopping Objectives in British Grocery Retail Transactions Using Segmented Topic Models
Applied Stochastic Models in Business and Industry, EarlyView.ABSTRACT Understanding the customer behaviours behind transactional data has high commercial value in the grocery retail industry. Customers generate millions of transactions every day, choosing and buying products to satisfy specific shopping needs.
Mariflor Vega Carrasco +4 more
wiley +1 more source