Results 91 to 100 of about 10,357 (300)

Hydrological Model Diversity Enhances Streamflow Forecast Skill at Short‐ to Medium‐Range Timescales

Water Resources Research, 2019
We investigate the ability of hydrological multimodel ensemble predictions to enhance the skill of streamflow forecasts at short‐ to medium‐range timescales.
Sanjib Sharma, Ridwan Siddique, Seann Reed, Peter Ahnert, Alfonso Mejia   +4 more
doaj   +1 more source

Spatial distribution of various forms of malnutrition among reproductive age women in Nepal: A Bayesian geoadditive quantile regression approach

, 2021
Umesh Ghimire, Richa Vatsa
openalex   +1 more source

Bayesian nonparametric quantile regression using splines

Computational Statistics & Data Analysis, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Paul A. Thompson, Yuzhi Cai, Rana Moyeed, Dominic Reeve, Julian Stander   +4 more
openaire   +3 more sources

Urban‐driven homogenization of aquatic subsidy size structure cascades to riparian predator communities

Oikos, EarlyView.
The export of emergent aquatic insects is a critical energy subsidy for terrestrial food webs. While urbanization is known to alter stream communities, its effects on the size structure of these insect subsidies and the subsequent consequences for riparian predators remain poorly understood.
Charles Gagnon, Louis‐Philippe Beauchamp, Eric Harvey   +2 more
wiley   +1 more source

Using a social‐ecological macrosystems framework to understand how human activities alter ecological synchrony

People and Nature, EarlyView.
Abstract Different aspects of ecological systems, biotic or abiotic, often fluctuate in coordinated patterns over space and time. Such high concordance between ecological processes is often referred to as ecological synchrony. Human activities, including and beyond climate change, have the potential to alter ecological synchrony by disrupting or ...
Yiluan Song, Mallory Barnes, K. Ann Bybee‐Finley, Kyla M. Dahlin, Travis McDevitt‐Galles, Stephan B. Munch, Guillermo E. Ponce‐Campos, Casey Youngflesh, Benjamin Zuckerberg, Kai Zhu   +9 more
wiley   +1 more source

Physics‐Informed Neural Networks for Battery Degradation Prediction Under Random Walk Operations

Quality and Reliability Engineering International, EarlyView.
ABSTRACT This study addresses the challenge of predicting the state of health (SoH) and capacity degradation in Battery Energy Storage Systems (BESS) under highly variable conditions induced by frequent control adjustments. In environments where random walk behavior prevails due to stochastic control commands, conventional estimation methods often ...
Alaa Selim, Huadong Mo, Hemanshu Pota, Daoyi Dong   +3 more
wiley   +1 more source

Improved Quantile Convolutional and Recurrent Neural Networks for Electric Vehicle Battery Temperature Prediction

Big Data Mining and Analytics
The battery thermal management of electric vehicles can be improved using neural networks predicting quantile sequences of the battery temperature. This work extends a method for the development of Quantile Convolutional and Quantile Recurrent Neural ...
Andreas M. Billert, Runyao Yu, Stefan Erschen, Michael Frey, Frank Gauterin   +4 more
doaj   +1 more source

Risk factors based vessel-specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: Results from the PARADIGM registry. [PDF]

Clin Cardiol, 2023
Park HB, Lee J, Hong Y, Byungchang S, Kim W, Lee BK, Lin FY, Hadamitzky M, Kim YJ, Conte E, Andreini D, Pontone G, Budoff MJ, Gottlieb I, Chun EJ, Cademartiri F, Maffei E, Marques H, Gonçalves PA, Leipsic JA, Shin S, Choi JH, Virmani R, Samady H, Chinnaiyan K, Stone PH, Berman DS, Narula J, Shaw LJ, Bax JJ, Min JK, Kook W, Chang HJ.   +32 more
europepmc   +1 more source

A Robust Self‐Starting Bayesian Approach for Multivariate Phase II Monitoring

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Traditional multivariate control charts require in‐control (IC) parameter estimates to be known or estimated from a large set of uncontaminated, historical Phase I observations. However, some processes need to be monitored when little Phase I data are available, and self‐starting approaches, including Bayesian methods, have proven useful. Self‐
Taylor R. Grimm, Kathryn B. Newhart, Amanda S. Hering   +2 more
wiley   +1 more source

A Sensitivity Analysis Workflow for Power Series Compounded Lifetime Models: Evidence From Weibull Power Series Fits

Quality and Reliability Engineering International, EarlyView.
ABSTRACT We propose a practical procedure to quantify the time varying influence of parameters on hazard functions for power series compounded lifetime models. The procedure combines likelihood based fitting with a two stage sensitivity analysis and applies to a range of baselines and compounding laws.
Yuancheng Si, Saralees Nadarajah
wiley   +1 more source