Results 61 to 70 of about 3,964 (194)

Multi‐Property Machine Learning Models to Accelerate the Transition Toward Bio‐Based Emulsion Polymers

Advanced Intelligent Discovery, EarlyView.
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary, Nicholas Ballard   +1 more
wiley   +1 more source

Optuna-Optimized Ensemble and Neural Network Models for Static Characteristics Prediction of Active Bearings with Geometric Adjustments

Modelling
Active vibration control designs for journal bearings have improved rotordynamic stability and led to advancements in adjustable bearing types that enable precise control of bearing geometry. In this study, optimized machine learning (ML) algorithms were
Girish Hariharan, Ravindra Mallya, Nitesh Kumar, Deepak Doreswamy, Gowrishankar Mandya Chennegowda, Subraya Krishna Bhat   +5 more
doaj   +1 more source

Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

Advanced Intelligent Discovery, EarlyView.
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang, Abudukadi Tudi, Ran An, Zhihua Yang   +3 more
wiley   +1 more source

Dynamic, Unconstrained Optimization of Secreted Enzyme Production in Fed‐Batch Fermentation Using Reinforcement Learning

Biotechnology and Bioengineering, EarlyView.
ABSTRACT Reinforcement learning (RL) has been used to control a wide range of dynamic processes, especially ones that are too complex to model well or have stochastic environmental perturbations. Fed‐batch fermentations are subject to changes in starting cell growth rates and process variations that can affect cell growth and secreted target production.
Sai Harish Uthravalli, Sakib Ferdous, J. Michael Hess, Nigel F. Reuel   +3 more
wiley   +1 more source

Explainable and Optuna-Optimized Machine Learning for Battery Thermal Runaway Prediction Under Class Imbalance Conditions

Thermo
Modern energy storage systems for both power and transportation are highly related to lithium-ion batteries (LIBs). However, their safety depends on a potentially hazardous failure mode known as thermal runaway (TR).
A. Abed, Ghalia Nassreddine, Obada Al-khatib, M. Nassereddine, A. Hellany   +4 more
semanticscholar   +1 more source

Enhancing Liver Cirrhosis Staging Accuracy using Optuna-Optimized TabNet

Journal of Applied Informatics and Computing
Liver cirrhosis is a progressive chronic disease whose early detection poses a clinical challenge, making accurate severity staging crucial for patient management.
Muhammad Farhan Arifin, Ika Novita Dewi, Abu Salam, Danang Wahyu Utomo, Sindhu Rakasiwi   +4 more
doaj   +1 more source

Analysis of Ruddlesden‐Popper and Dion‐Jacobson 2D Lead Halide Perovskites Through Integrated Experimental and Computational Analysis

Battery Energy, Volume 4, Issue 2, March 2025.
Optimized ML framework for predicting RP and Dj phases in perovskite solar cells. ABSTRACT Two‐dimensional (2D) lead halide perovskites (LHPs) have captured a range of interest for the advancement of state‐of‐the‐art optoelectronic devices, highly efficient solar cells, next‐generation energy harvesting technologies owing to their hydrophobic nature ...
Basir Akbar, Kil To Chong, Hilal Tayara
wiley   +1 more source

Slope Stability Assessment Using an Optuna-TPE-Optimized CatBoost Model

Engineer
Slope stability assessment is a critical component of engineering safety. Conventional analytical methods frequently struggle to integrate heterogeneous slope data and model intricate failure mechanisms, thereby constraining their efficacy in practical ...
Liang Wang, Chengliang Zhang, Wei Wang, Tao Deng, T. Ma, P. Shuai   +5 more
semanticscholar   +1 more source

Comparative Analysis of Automated Machine Learning for Hyperparameter Optimization and Explainable Artificial Intelligence Models

IEEE Access
Artificial intelligence (AI) has been increasingly applied to solve complex real-world problems. One of the most significant challenges in AI lies in selecting and fine-tuning the optimal algorithm for a given task.
Muhammad Salman Khan, Tianbo Peng, Hanzlah Akhlaq, Muhammad Adeel Khan   +3 more
doaj   +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