Results 171 to 180 of about 36,835 (256)

Ensemble genetic and CNN model-based image classification by enhancing hyperparameter tuning. [PDF]

Sci Rep
Hussain W, Mushtaq MF, Shahroz M, Akram U, Ghith ES, Tlija M, Kim TH, Ashraf I.   +7 more
europepmc   +1 more source

Physics‐encoded transfer learning for scale‐up modeling of CHO cell bioreactors

AIChE Journal, EarlyView.
Abstract Developing reliable predictive models for mammalian cell bioreactors, particularly Chinese hamster ovary (CHO) cultures widely used in biopharmaceutical manufacturing, remains challenging due to severe data scarcity in industrial‐scale reactors.
Muyang Li, Ming Xiao, Zhe Wu
wiley   +1 more source

An intelligent fault diagnosis model for bearings with adaptive hyperparameter tuning in multi-condition and limited sample scenarios. [PDF]

Sci Rep
Li J, Huang Z, Jiang L, Zhang Y.
europepmc   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Retraction Note: Hybrid CNN-LSTM model with efficient hyperparameter tuning for prediction of Parkinson's disease. [PDF]

Sci Rep
Lilhore UK, Dalal S, Faujdar N, Margala M, Chakrabarti P, Chakrabarti T, Simaiya S, Kumar P, Thangaraju P, Velmurugan H.   +9 more
europepmc   +1 more source

Limitations of Foundation Models in Energy Materials Simulations: A Case Study in Polyanion Sodium Cathode Materials

Advanced Intelligent Discovery, EarlyView.
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen, Chiku Parida, Jonas Busk, Jin Hyun Chang, Arghya Bhowmik, Juan Maria Garcia Lastra   +5 more
wiley   +1 more source

Lightweight convolutional neural networks using nonlinear Lévy chaotic moth flame optimisation for brain tumour classification via efficient hyperparameter tuning. [PDF]

Sci Rep
Dehkordi AA, Neshat M, Khosravian A, Thilakaratne M, Safaa Sadiq A, Mirjalili S.   +5 more
europepmc   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Gesture recognition for hearing impaired people using an ensemble of deep learning models with improving beluga whale optimization-based hyperparameter tuning. [PDF]

Sci Rep
Assiri M, Selim MM.
europepmc   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source