Real-time inverse dynamic deep neural network tracking control for Delta robot based on a COVID-19 optimization
M Shamseldin - Journal of Robotics and Control (JRC), 2023 - journal.umy.ac.id
This paper presents a new technique to design an inverse dynamic model for a delta robot
experimental setup to obtain an accurate trajectory. The input/output data were collected …
experimental setup to obtain an accurate trajectory. The input/output data were collected …
[HTML][HTML] A Robust Machine Learning Model for Diabetic Retinopathy Classification
Ensemble learning is a process that belongs to the artificial intelligence (AI) field. It helps to
choose a robust machine learning (ML) model, usually used for data classification. AI has a …
choose a robust machine learning (ML) model, usually used for data classification. AI has a …
[HTML][HTML] Predicting an Optimal Medication/Prescription Regimen for Patient Discordant Chronic Comorbidities Using Multi-Output Models
This paper focuses on addressing the complex healthcare needs of patients struggling with
discordant chronic comorbidities (DCCs). Managing these patients within the current …
discordant chronic comorbidities (DCCs). Managing these patients within the current …
Multi-period early-warning precipitation identification method for the easily waterlogged districts in Jiangxi province, China
H Bai, B Wang, B Li, Z Liu, Z Wen, Y Zhang… - Theoretical and Applied …, 2024 - Springer
Urban easily waterlogged districts need more systematic monitoring as the key disaster-
forming and managing spatial scale, hard to identify the early-warning precipitation (EP). We …
forming and managing spatial scale, hard to identify the early-warning precipitation (EP). We …