Results 211 to 220 of about 1,179 (264)

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

Ruijsenaars wavefunctions as modular group matrix coefficients. [PDF]

Lett Math Phys
Di Francesco P, Kedem R, Khoroshkin S, Schrader G, Shapiro A.   +4 more
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

Comparative analysis of lump, breather, and interaction solutions using a bidirectional data mapping approach. [PDF]

Sci Rep
Kazmi SS, Riaz MB.
europepmc   +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

Privacy-preserving computation scheme for the maximum and minimum values of the sums of keyword-corresponding values in cross-chain data exchange. [PDF]

Sci Rep
Liu X, Gao H, Luo D, Ye W, Jia L, Xu G, Chen X, Liang L, Zhang B, Gu Y.   +9 more
europepmc   +1 more source

Asymptotic properties of cross‐classified sampling designs

Canadian Journal of Statistics, EarlyView.
Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley   +1 more source

Differentiable modeling and optimization of non-aqueous Li-based battery electrolyte solutions using geometric deep learning. [PDF]

Nat Commun
Zhu S, Ramsundar B, Annevelink E, Lin H, Dave A, Guan PW, Gering K, Viswanathan V.   +7 more
europepmc   +1 more source

Nonlinear permuted Granger causality

Canadian Journal of Statistics, EarlyView.
Abstract Granger causality is an established, contentious method that seeks causal temporal connections via association and precedence. While not true causal inference, it assists in mapping networks of information flow that may warrant further study.
Noah D. Gade, Jordan Rodu
wiley   +1 more source

Mapping research trends in macrophage polarization and immunotherapeutic potential in prostate cancer: a bibliometric and visual analysis. [PDF]

Front Oncol
Wu P, Chen L, Yang J, He C, Tang A, Yang Y.   +5 more
europepmc   +1 more source