Results 241 to 250 of about 3,667,438 (313)
Merging computational fluid dynamics and 4D Flow MRI using proper orthogonal decomposition and ridge regression. [PDF]
J Biomech, 2017 Bakhshinejad A +5 more
europepmc +1 more source
Energy Science &Engineering, EarlyView.By manipulating current and voltage measurements, an assailant can induce unwanted relay action while attempting to avoid detection. Detecting advanced cyber intrusions in power protection environments requires specialised data analysis and anomaly detection methods.
Feras Alasali +6 more
wiley +1 more source
Forecasting COVID-19 Outbreak Progression Using Hybrid Polynomial-Bayesian Ridge Regression Model
, 2020 Saqib M.
europepmc +1 more source
Energy Consumption and CO2 Emissions Forecasting of Transport Sector Using Machine Learning
Energy Science &Engineering, EarlyView.The transport sector accounts for approximately one‐quarter of Iran's final energy consumption. The energy demand in this sector has the least variation, with petroleum products accounting for more than 85% of the demand. Furthermore, the accelerated growth of energy consumption and the sector's reliance on fossil fuels, which are the main cause of ...
Amir Hossein Akbari +2 more
wiley +1 more source
Energy Science &Engineering, EarlyView.This graphical abstract summarizes the proposed framework for improving short‐term residential natural gas consumption forecasting by integrating a novel socioeconomic indicator, the subscription growth ratio (SGR), with conventional meteorological variables.
Ali Pirzad, Mostafa Khanzadi
wiley +1 more source
Anuran call properties as reliable indicators of environmental suitability for reproduction
Frontiers in Ecology and the Environment, EarlyView.The onset of animal breeding activity is often accompanied by auditory signals, typically produced by males, that indicate reproductive status to potential mates and competitors. Here, using male anuran advertisement calls as a case study, we present the novel hypothesis that characteristics of ectotherm auditory signals that are modulated by ...
Julianne E Pekny +2 more
wiley +1 more source
Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices
Journal of Forecasting, EarlyView.ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer +3 more
wiley +1 more source
Random Integrated Subdata Ensemble Method for Key Variable Selection in Rare Event Setting
Journal of Forecasting, EarlyView.ABSTRACT We propose a general variable selection procedure to identify key input variables by applying elastic net regression to representative subdata in place of the full sample to select variables. We combine the lists of selected variables from each subdata through ensemble techniques, using the frequency of selecting the variable across different ...
Ching‐Chi Yang +3 more
wiley +1 more source
Forecasting House Prices: The Role of Market Interconnectedness
Journal of Forecasting, EarlyView.ABSTRACT While the existing research uncovers interconnections between various housing markets, it largely ignores the question of whether such linkages can improve house price predictions. To address this issue, we proceed in two steps. First, we forecast disaggregated house price growth rates from Australia and China to determine whether ...
Zac Chen +3 more
wiley +1 more source
Intraday Functional PCA Forecasting of Cryptocurrency Returns
Journal of Forecasting, EarlyView.ABSTRACT We study the functional PCA (FPCA) forecasting method in application to functions of intraday returns on Bitcoin. We show that improved interval forecasts of future return functions are obtained when the conditional heteroscedasticity of return functions is taken into account.
Joann Jasiak, Cheng Zhong
wiley +1 more source