Results 181 to 190 of about 296,811 (276)

Predicting Visual Field Loss in Glaucoma Using OCT and Deep Learning: A Comparative Study of U-Net Variants. [PDF]

Ophthalmol Sci
Ohn K, Hwang J, Jung J, Whang WJ.
europepmc   +1 more source

Box–Behnken optimization and ANN‐ANFIS integrated modelling for transesterification using thermally activated basic oxygen furnace slag catalyst

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract Global energy demand and environmental concerns have intensified the search for renewable and sustainable energy sources. This study thus, focuses on optimizing the transesterification process of waste cooking oil (WCO) using thermally activated basic oxygen furnace slag catalyst calcined at 850°C (BOF 850). The optimization and modelling were
Johra S. Ali, Hillary L. Rutto
wiley   +1 more source

Channel estimation strategies for STAR-RIS-Aided NOMA: robustness to imperfections and complexity trade-offs for 6G wireless systems. [PDF]

Sci Rep
Ammisetty MB, Ramarakula M.
europepmc   +1 more source

Application of artificial neural network and general machine learning modelling on CO2 adsorption in moisture equilibrated South African high and medium rank coals

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract This study investigates the effect of moisture on CO2 adsorption in South African coals using both experimental and machine learning approaches. Three coal samples (SL, TN, and EM) with varying ranks (RoVmr: 3.49%, 1.26%, and 0.64%, respectively) were collected from different regions of South Africa.
Kasturie Premlall, Lawrence Koech, Douw Faurie, Khanyisile Lepota   +3 more
wiley   +1 more source

On Optimal Multichannel Mean-Squared Error Estimators for Speech Enhancement

IEEE Signal Processing Letters, 2009
R. Hendriks, R. Heusdens, U. Kjems, J. Jensen   +3 more
semanticscholar   +1 more source

Harnessing machine learning and optimization for informed chemical engineering decisions: A styrene reactor analysis

The Canadian Journal of Chemical Engineering, EarlyView.
This study shows that integrating multiple machine learning models with optimization and decision‐making improves chemical process design, and that a consensus‐based strategy across models provides more robust and reliable operating recommendations than any single model, especially under limited or noisy data conditions.
Farough Agin, Clémence Fauteux‐Lefebvre, Jules Thibault   +2 more
wiley   +1 more source

Stochastic Grey Wolf Optimization for Hyperparameter Tuning of LSTM and RNN Models in Energy Forecasting. [PDF]

Sci Rep
Albser OA, Mouhamed MR, Shatta SA, Sweilem NH, Darwish A.   +4 more
europepmc   +1 more source

Lower bound on the mean-squared error in oversampled quantization of periodic signals using vector quantization analysis

IEEE Transactions on Information Theory, 1996
N. T. Thao, M. Vetterli
semanticscholar   +1 more source

Jackknife bias‐corrected variance estimation for the generalized regression estimator

Canadian Journal of Statistics, EarlyView.
Abstract Commonly used variance estimators for the generalized regression estimator (GREG) are based on Taylor linearization and jackknife. Traditionally, a jackknife GREG variance estimator is obtained by jackknifing GREG, which consists of computing GREG from each of several subsamples of the parent sample, and estimating the variance of the parent ...
Marius Stefan, J.N.K Rao
wiley   +1 more source

A partial envelope approach for modelling multivariate spatial‐temporal data

Canadian Journal of Statistics, EarlyView.
Abstract In the new era of big data, modelling multivariate spatial‐temporal data is a challenging task due to both the high dimensionality of the features and complex associations among the responses across different locations and time points.
Reisa Widjaja, Wenbo Wu, Victor De Oliveira, Keying Ye   +3 more
wiley   +1 more source