Results 181 to 190 of about 50,437 (269)

High‐Dimensional Cumulative Sum Control Charts for Industrial Measurement Systems

Quality and Reliability Engineering International, EarlyView.
ABSTRACT High dimensional sensing in modern factories and energy assets produces thousands of correlated signals. Detecting small process shifts is challenging because many classical multivariate charts lose power or become unstable. We present two cumulative sum procedures for two sample monitoring that remain effective when the number of variables is
Osama Alhadi, Tahir Mahmood, Muhammad Riaz, Nasir Abbas   +3 more
wiley   +1 more source

Improving the estimation accuracy of rice leaf protein nitrogen using data augmentation, explainable machine learning, and UAV hyperspectral imagery. [PDF]

Front Plant Sci
Peng Y, Tu Y, Xu Y, Zhong W, Li Z, Liang J, Huang J.   +6 more
europepmc   +1 more source

Not All Missing Data are Equal: Choosing the Right Imputation Method for Binary Datasets

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Missing binary predictors are common in reliability, quality control, and industrial decision systems, yet imputation methods are often chosen by convenience rather than evidence. We conduct a Monte Carlo study comparing mode substitution, sequential hot‐deck, missForest, MICE, and KNN with three neighbourhood sizes under MCAR, MAR, and MNAR ...
Manuel Delfino, Fabio Rapallo
wiley   +1 more source

A Review and Experimental Analysis of Supervised Learning Systems and Methods for Protein-Protein Interaction Detection. [PDF]

Int J Mol Sci
Taha K.
europepmc   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

Responsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen, Siwei Yang, Xiangqian Cui, Ziheng Liu, Hang Wang, Yongqiang Li, Peng He, Miao Wang, Guqiao Ding   +8 more
wiley   +1 more source

Machine Learning-Based Accurate Full-Sib Family Assignment in Sturgeon Using Whole-Genome Sequencing Data. [PDF]

Int J Mol Sci
Yan J, Li H, Dong T, Wang W, Yan X, Bai S, Song H, Hu H.   +7 more
europepmc   +1 more source

Ecological and Technological Insights to Enhance Rice Production: A Machine Learning Approach for Sustainable Agriculture in Granma, Cuba

Sustainable Development, EarlyView.
ABSTRACT Amid the quest for sustainable agriculture, this study explores key ecological and technological factors influencing crop production under climate change. We conduct a comprehensive assessment of temperature, biomass, farmer education, renewable energy devices, greenhouse gas emissions and their effects on rice yields in Granma, Cuba, from ...
Afzal Ahmed Dar, Zhi Chen, Sergio RodrIguez‐Rodríguez, Fariborz Haghighat, Chunjiang An, Roberto Alejandro García Reyes, Beatriz González‐Rosales   +6 more
wiley   +1 more source

Unified comparison of machine learning paradigms for blood transfusion prediction in pediatric congenital heart surgery. [PDF]

iScience
Yin MW, Li J, Huang J, Zhu Z, Chen BH, Shi Z, Jiang Q, Chen XJ, Yu G.   +8 more
europepmc   +1 more source

From Prediction to Prevention: An Explainable GeoAI Framework for Flood Susceptibility and Urban Exposure Assessment Using Machine and Deep Learning Models

Sustainable Development, EarlyView.
ABSTRACT Rapid urbanisation and intensifying rainfall have increased cities' vulnerability to flooding, posing major challenges to sustainable development. Although machine learning models have improved flood prediction accuracy, most remain limited by their black‐box nature and lack of actionable insights.
Abdulwaheed Tella, Izni Zahidi, Chow Ming Fai, Chukwuma Okolie, Quoc Bao Pham   +4 more
wiley   +1 more source