Optimized stacking ensemble models for the prediction of diabetic progression

D VK, TK Ramesh - Multimedia Tools and Applications, 2023 - Springer
The influence of applied machine learning in our day-to-day life has seen significant
improvement over the last few years. The use of machine learning in Artificial Intelligence to …

Data-driven sales optimization with regression and chaotic pattern search

SR Gaddam, S Jayan, P Ravi, B Alatas - PeerJ Computer Science, 2024 - peerj.com
Lead generation is the process of gaining potential customers' interest to increase future
sales, and it is an essential part of many businesses'(amusement parks, theme parks, clubs …

Machine learning techniques for vector control of permanent magnet synchronous motor drives

AM Tom, JL Febin Daya - Cogent Engineering, 2024 - Taylor & Francis
In the conventional vector control technique for motor drive, Proportional-Integral (PI)
controllers are being used, which are sensitive to parameter variations of the drive system …

Modeling hot deformation of 5005 aluminum alloy through locally constrained regression models with logarithmic transformations

J Cho, SH Song - Applied Sciences, 2021 - mdpi.com
This study presents the adoption of locally constrained regression models (LCRMs) with
logarithmic transformations in order to model the flow stress behavior of the high …

A Dynamic Cost-Efficient Task Offloading Framework for Resource-Constrained Edge-Based Smart Healthcare Systems

SS Tripathy, S Bebortta, A Nayak… - … Conference on Artificial …, 2023 - ieeexplore.ieee.org
The advancements in Internet of Healthcare Things (IoHT) has significantly transformed the
healthcare industry. To meet the computing needs of the healthcare industry, the Multi …

Prognostic Modeling of Diabetes Mellitus in Women: A comparitive analysis of Machine Learning algorithms integrating Clinical and Genetic Data

MV Prashanth, NT Jose, KH Verma… - … in Computer Science …, 2024 - ieeexplore.ieee.org
Diabetes is considered as one of the most commonly observed medical condition among
human beings. Millions of people worldwide are affected by a chronic condition that goes by …

Deep Learning-Based Continuous Glucose Monitoring with Diabetic Prediction Using Deep Spectral Recurrent Neural Network

G Kiruthiga, L Shakkeera, A Asha, B Dhiyanesh… - International Conference …, 2023 - Springer
It is estimated that approximately 50% of the world's population has diabetes mellitus.
Diabetic diseases are caused by either a lack of insulin produced by the pancreas or a lack …

Diabetic prediction framework using optimisation strategy via optimal weighted score-based deep ensemble network to support diabetic patients

SK Bejugam, J Vankara - International Journal of …, 2023 - inderscienceonline.com
Diabetes is one of the dangerous diseases that increase blood glucose levels, and it affects
the patient's life. Next, in the deep feature extraction stage, the collected data is employed as …

Vector Control of PMSM Drive in Electric Vehicles Using SVM Regression Approach

AM Tom, JL Febin Daya - International Conference on Communication and …, 2022 - Springer
A surface permanent magnet synchronous motor (PMSM) drive system with a support vector
machine (SVM)-based current controller is presented in this study. Proportional-Integral (PI) …

[PDF][PDF] Machine Learning-Based Diabetic Disease Prediction With Big Healthcare Data

S Seka, K Pon, S Shakila - Webology, 2021 - webology.org
Big data is a collection of large volume of structured and unstructured data. With
development of standards, diabetes is increasingly common in people daily life. Diabetes is …