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 +3 more
wiley +1 more source
A Computational Workflow for Cell Line Profiling by Imaging Mass Cytometry
Cytometry Part A, EarlyView.ABSTRACT In single‐cell spatial phenotyping biology, imaging mass cytometry (IMC) stands out as a cutting‐edge, highly multiplexed technology driving discoveries across various disease areas. In vitro profiling relies on tumor‐derived cancer cell lines, known for their diverse morphologies and phenotypes.
Alexandre Bouzekri +2 more
wiley +1 more source
Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN
Deep Underground Science and Engineering, EarlyView.A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan +4 more
wiley +1 more source
AI‐Driven Precision Annealing for High Performance Fe‐Based Amorphous Alloys
ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.The four stages of the research process are as follows: First, data is collected and a database is constructed. This is followed by feature selection and analysis, then the establishment of machine learning models, and finally formulation design and preparation.
Yichuan Tang +13 more
wiley +1 more source
Mechanistic Origins of Structural Failure in Deeply‐Lithiated LixMoS2
ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.Global optimization and ab initio molecular dynamics reveal how Li drives the 2H to 1T′ phase transformation in MoS2 and where the layered framework begins to fracture. Controlled pre‐lithiation stabilizes 1T′ and significantly delays the onset of structural failure, while opening out‐of‐plane Li pathways, offering design rules for robust, high‐rate ...
Gunyoung Heo +4 more
wiley +1 more source
Ensemble Deep Learning–Based Wind Power Forecasting With Self‐Adaptive Osprey Optimization Algorithm
Energy Science &Engineering, EarlyView.Design of Self‐Adaptive Osprey (SAO) algorithm: The novel SAO algorithm is designed by integrating the exploration capability of the conventional Osprey algorithm by including the self‐adaptiveness for enhancing the convergence rate. Ensemble Deep Learning for wind power forecasting: The wind forecasting is employed using the proposed Ensemble learning
Johncy Bai Johnson +3 more
wiley +1 more source
Detecting Malicious URLs Using Classification Algorithms in Machine Learning and Deep Learning
Syrian Journal for Science and InnovationDue to the daily necessity of using links and websites and the high prevalence of malicious URLs, many security threats arise for Internet users and organizations.
Sira Astour, Ahmad Hasan
doaj
Integration of PCG spectrogram texture and deep features for the diagnosis of heart failure with preserved ejection fraction using heterogeneous stacking ensemble learning. [PDF]
Front PhysiolZheng Y, Qin J, Lv F, Li X, Guo X.
europepmc +1 more source
An interpretable stacking ensemble learning framework based on multi-dimensional data for real-time prediction of drug concentration: The example of olanzapine. [PDF]
Front Pharmacol, 2022 Zhu X +5 more
europepmc +1 more source
Energy Science &Engineering, EarlyView.Interpretable tree‐based models integrate microseismic, geological, and mining indicators to predict short‐term rockburst risk. SHAP analysis reveals the dominant role of energy‐related features and clarifies nonlinear factor interactions, enabling transparent and reliable early‐warning in deep coal mines.
Shuai Chen +4 more
wiley +1 more source