A fusion data preprocessing method and its application in complex industrial power consumption prediction
Sign Up to like & getrecommendations! Published in 2021 at "Mechatronics"
DOI: 10.1016/j.mechatronics.2021.102520
Abstract: Abstract Data-driven prediction methods often encounter problems in industrial applications due to noise, data redundancy, and insufficient labeled data. Preprocessing the data is required to improve prediction accuracy. At present, most data preprocessing methods are… read more here.
Keywords: consumption prediction; power consumption; fusion data; data preprocessing ... See more keywords
ResNet incorporating the fusion data of RGB & hyperspectral images improves classification accuracy of vegetable soybean freshness
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-51668-6
Abstract: The freshness of vegetable soybean (VS) is an important indicator for quality evaluation. Currently, deep learning-based image recognition technology provides a fast, efficient, and low-cost method for analyzing the freshness of food. The RGB (red,… read more here.
Keywords: classification; fusion data; resnet; rgb hyperspectral ... See more keywords
Interpretable machine learning models based on multi-dimensional fusion data for predicting positive surgical margins in robot-assisted radical prostatectomy: a retrospective study
Sign Up to like & getrecommendations! Published in 2025 at "Frontiers in Oncology"
DOI: 10.3389/fonc.2025.1661695
Abstract: Objective This study aimed to develop and validate interpretable machine learning (ML) models based on multi-dimensional fusion data for predicting positive surgical margins (PSM) in robot-assisted radical prostatectomy (RARP). Methods Patients who underwent RARP at… read more here.
Keywords: dimensional fusion; fusion data; validation; model ... See more keywords