Results 181 to 190 of about 145,710 (264)

Machine learning-based prediction of well performance parameters for wellhead choke flow optimization. [PDF]

Sci Rep
Akbari A, Ghazi F, Kazemzadeh Y.
europepmc   +1 more source

Predicting solar cell efficiencies using historical data from a manufacturing process

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract The solar cell manufacturing data of a passivated emitter and rear cell solar cell manufacturing plant was studied to assess the effects of tool usage and the processing time spent on each tool on the solar cell efficiency. Since manufacturing processes involve several steps with multiple tools, tracing their quality parameters back to the ...
Sushmita Mittra, Vinay Prasad
wiley   +1 more source

Forecasting mean deviation in glaucoma patients using an irregular autoregressive time series method. [PDF]

Sci Rep
Childress C, Gardiner SK, Pathak M.
europepmc   +1 more source

Random forest regression for catalyst performance prediction and validation of tri‐reforming of methane (TRM)

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract Carbon dioxide‐reduced hydrogen can be synthesized through various methods such as dry‐reforming (DRM), steam reforming (SMR), and partial oxidation (POX). Tri‐reforming of methane (TRM) is a promising technology which combines all the above‐mentioned processes for the simultaneous production of hydrogen and syngas with high energy efficiency.
Paulo A. L. de Souza, Raja Muhammad Afzal, Felipe Gomes Camacho, Nader Mahinpey   +3 more
wiley   +1 more source

Frequency-aligned loss and spectral filtering improve long-range influenza forecasting. [PDF]

Front Public Health
Feng T, Luo C, Huang Y.
europepmc   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

The Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos, Heleno Bispo, Thiago Vaz da Costa, Sérgio Mauro da Silva Neiro   +3 more
wiley   +1 more source

Leveraging machine learning for accurate forecasting of pulmonary tuberculosis epidemics in a coastal city in China. [PDF]

Trop Med Health
Yang J, Pan J, Chen J, Xu Y, Zhang X.
europepmc   +1 more source

Safety soft sensor development for pilot‐scale ilmenite electric arc furnace using long short‐term memory‐based architecture

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract Ilmenite electric arc furnaces (EAFs) are used for smelting titanium‐iron oxide ore at high temperatures generated by electrical arcs to produce titanium slag and pig iron. As these units are pushed to their limits, ensuring safe and reliable operation becomes challenging.
Antony Gareau‐Lajoie, Djogap F. Chrysler J., Daniel Rodrigues, Marie‐Ève Gosselin, Moncef Chioua   +4 more
wiley   +1 more source

Enhancing rabies epidemic modeling with neural networks and fractional calculus. [PDF]

Sci Rep
Shafqat R, Imran, Al-Quran A, Djaouti AM.   +3 more
europepmc   +1 more source