Results 41 to 50 of about 4,489 (189)

Power Prediction of Photovoltaic Power Generation Based on Improved Gaussian Process Regression Modeling

Taiyuan Ligong Daxue xuebao
Purposes The proportion of photovoltaic(PV) power generation has been increasing in China. PV power generation is greatly affected by meteorological factors and its output power shows strong intermittency and volatility because of the complexity and ...
XIAO Chun, HAO Junbo, YANG Xiaoxia, HAN Xiaoqing   +3 more
doaj   +1 more source

Non-Linear Dimensionality Reduction and Gaussian Process Based Classification Method for Smoke Detection

IEEE Access, 2017
To improve smoke detection accuracy, we combine local binary pattern (LBP) like features, kernel principal component analysis (KPCA), and Gaussian process regression (GPR) to propose a novel data processing pipeline for smoke detection.
Feiniu Yuan, Xue Xia, Jinting Shi, Hongdi Li, Gang Li   +4 more
doaj   +1 more source

Extrusion Bioprinting for Wound Healing: Innovations in Functionalized Bioinks and Bioprinting Technology

Advanced Materials Technologies, EarlyView.
Extrusion‐based bioprinting (EBB) has emerged as a versatile biofabrication platform capable of precisely depositing bioinks composed of biomaterials, cells, and bioactive agents to generate patient‐specific, biomimetic skin constructs. This paper presents a state‐of‐the‐art and forward‐looking overview of EBB for wound healing, encompassing printing ...
Hien‐Phuong Le, Anh Tuan Trong Tran, Ammara Waheed, Tran Thanh Tung, Dusan Losic   +4 more
wiley   +1 more source

Machine Learning for Green Solvents: Assessment, Selection and Substitution

Advanced Science, EarlyView.
Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta, Janhavi Nistane, Abhishek Sose, Harikrishna Sahu, Rampi Ramprasad   +4 more
wiley   +1 more source

Deck motion prediction using neural kernel network Gaussian process regression

Xibei Gongye Daxue Xuebao
Deck motion prediction and compensation are critical technologies for carrier-based aircraft automatic landing. Traditional deck motion prediction methods rely on precision of motion models and parameter adjustments, facing challenges in adaptability to ...
QIN Peng, LUO Jianjun, MA Weihua, WU Liming   +3 more
doaj   +1 more source

Novel Hybridized Computational Paradigms Integrated with Five Stand-Alone Algorithms for Clinical Prediction of HCV Status among Patients: A Data-Driven Technique

Life, 2022
The emergence of health informatics opens new opportunities and doors for different disease diagnoses. The current work proposed the implementation of five different stand-alone techniques coupled with four different novel hybridized paradigms for the ...
Zachariah Madaki, Nurettin Abacioglu, A. G. Usman, Neda Taner, Ahmet. O. Sehirli, S. I. Abba   +5 more
doaj   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Automation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations

Advanced Science, EarlyView.
Successful antibody formulation necessitates balancing factors such as thermal stability, colloidal stability, and viscosity across a vast excipient design space. This work integrates robotic liquid handling, high‐throughput biophysical characterization, and multi‐objective Bayesian optimization in an iterative closed‐loop Design‐Build‐Test‐Learn cycle.
D. Christopher Radford, Matthew Tamasi, Elena Di Mare, Adam J. Gormley   +3 more
wiley   +1 more source

Prediction of mean wave overtopping at simple sloped breakwaters using kernel-based methods

Journal of Hydroinformatics, 2021
The accurate prediction of the mean wave overtopping rate at breakwaters is vital for a safe design. Hence, providing a robust tool as a preliminary estimator can be useful for practitioners.
Shabnam Hosseinzadeh, Amir Etemad-Shahidi, Ali Koosheh   +2 more
doaj   +1 more source

Human‐Guided Bayesian Optimization Enables High‐Throughput Laser Annealing of Mesoporous SiOx Anodes for Lithium‐Ion Batteries

Advanced Science, EarlyView.
An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park, Yeongje Lee, Sunho Jeong, Eungkyu Lee   +3 more
wiley   +1 more source