… investigates electric vehicle (EV) charging behavior and … used machine learning algorithms
to predict charging behavior, … The three methods are assembled as the proposed Ensemble …

… DL based methods to predict EV user behavior. In this paper, we predict EV user behavior
using ML and DL methods … Gadh, “Ensemble machine learning-based algorithm for electric …

… in smart city applications, electric vehicles (EVs) are becoming … We trained four popular ML
models along with two ensemble … optimal vehicle grid integration strategy with user behavior …

Electric vehicles may reduce greenhouse gas emissions from … using machine learning
models— Gradient Boosting Classifier and Random Forest Classifier. Since both are ensemble …

… Ensemble machine learning models with base models as Random Forest (RF), Support …
of EV user behavior which are considered in this work. EV user behavior objective can be …

… , and ensemble machine learning were assessed in and compared in [10] yielding the
ensemble … We propose a method to increase the user behavior prediction reliability by exploiting …

… behavior throughout trips. Drivers should be well aware of the remaining charging time in
advance based on their vehicle's … to better understand the charging behavior of EV drivers. …

… EVSE (Electric Vehicle Supply Equipment) … Machine learning entails optimizing for a
particular metric, such as mean-absolute errors. Typically, we train a single model or an ensemble …

… As discussed in this paper, the EV user behavior is … user behavior: Random Forest (RF)
regression, Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), ensemble …

… for the use of supervised and unsupervised Machine Learning … , ‘‘Ensemble machine
learning-based algorithm for electric … Gadh, ‘‘Electric vehicle user behavior prediction using hybrid …