… This paper addresses these issues and presents a novel genetic algorithmbased bagging
ensemble model. The best features have been chosen using various methods that correlate …

… ensemble that enhances network classification performance. Constructing a foundational
classifier ensemble entails rearranging training datasets and assigning a base classifier to …

… Activity Recognition is widely regarded as the most popular methodology within the field of
Ambient Assisted Living. Human Activity Recognition … Wrapper method selects the optimal …

… classification accuracy, convergence speed, and convergence precision than other
compared approaches in optimizing … for selecting the optimal features for the classification of …

… optimization (PSO) and SVM classifier for tunning the parameters in order to propose an
intrusion detection … The intrusion feature selection algorithm based on PSO [57,67] is the New …

… A knowledge-driven approach to activity recognition in smart homes. IEEE … Genetic
Algorithm-based Classifier Ensemble Optimization for Activity Recognition in Smart Homes…

… The online phase involves activity recognition and … [52] presented a continual learning
classification algorithm based … householders’ cooking activities in two smart houses with different …

… devices for the elderly, smart home appliances, VR glasses … classifier for action recognition
[18, 19]. It is proposed to use … optimization is proposed and applied to the algorithm based …

… is introduced for smart homes to optimize the energy cost in peak hours. Furthermore, the
proposed solution establishes the coordination among the smart appliances and mitigates the …

… Activity recognition aims to identify actions and activities that … In the second stage, we propose
a novel clustering algorithm based … in user activity from unlabelled smart home sensor data …