Electric Vehicle Charge Classification Technique For Optimized Battery Charge Based On Ml
The severity of ischaemic stroke ,the world Intricate connection in the 5110 patient health profiles Leading cause of death and disability ,can be that made up the health care dataset. Three potent Considerably decreased by early detection of stoke . Classifiers light gradient boosting machine(LGBM), The purpose of this research is to use cutting edge extreme gradient boosting(XGBoost),random forest Machine learning techniques to create a predictive (RF)_were integrated to create a stacking ensemble Model for ischaemic strock. This method u.se an model that improved the prediction capacity. Artificial neutral network(ANN).
Authors
- Imran Ahmad Siddiqui (ORCID: https://orcid.org/0000-0001-7688-295X)
- Agus Jamal (ORCID: https://orcid.org/0000-0002-2576-8150)
- M. A. Mannan (ORCID: https://orcid.org/0000-0002-9626-2560)
- Bilal Rasheed
Institutions
- English and Foreign Languages University (IN)
- Autonomous University of Lisbon (PT)
Publication Details
- Journal
- International jounal of information technology and computer engineering.
- Published
- 2025-06-12
- DOI
- https://doi.org/10.62647/ijitce2025v13i2spp146-151
- Primary Topic
- Advanced Battery Technologies Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00