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Wireless powered mobile edge computing networks: A survey
Wireless Powered Mobile Edge Computing (WPMEC) is an integration of Mobile Edge
Computing (MEC) and Wireless Power Transfer (WPT) technologies, to both improve …
Computing (MEC) and Wireless Power Transfer (WPT) technologies, to both improve …
A survey on evolutionary multiobjective feature selection in classification: approaches, applications, and challenges
Maximizing the classification accuracy and minimizing the number of selected features are
two primary objectives in feature selection, which is inherently a multiobjective task …
two primary objectives in feature selection, which is inherently a multiobjective task …
Survey on evolutionary deep learning: Principles, algorithms, applications, and open issues
Over recent years, there has been a rapid development of deep learning (DL) in both
industry and academia fields. However, finding the optimal hyperparameters of a DL model …
industry and academia fields. However, finding the optimal hyperparameters of a DL model …
Partial reinforcement optimizer: an evolutionary optimization algorithm
In this paper, a novel evolutionary optimization algorithm, named Partial Reinforcement
Optimizer (PRO), is introduced. The major idea behind the PRO comes from a psychological …
Optimizer (PRO), is introduced. The major idea behind the PRO comes from a psychological …
Boosting precision crop protection towards agriculture 5.0 via machine learning and emerging technologies: A contextual review
Crop protection is a key activity for the sustainability and feasibility of agriculture in a current
context of climate change, which is causing the destabilization of agricultural practices and …
context of climate change, which is causing the destabilization of agricultural practices and …
Feature selection using diversity-based multi-objective binary differential evolution
By identifying relevant features from the original data, feature selection methods can
maintain or improve the classification accuracy and reduce the dimensionality. Recently …
maintain or improve the classification accuracy and reduce the dimensionality. Recently …
Machine learning for uav-aided its: A review with comparative study
Unmanned Aerial Vehicles (UAVs) have immense potential to enhance Intelligent Transport
Systems (ITS) by aiding in real-time traffic monitoring, emergency response, and …
Systems (ITS) by aiding in real-time traffic monitoring, emergency response, and …
A survey on learnable evolutionary algorithms for scalable multiobjective optimization
Recent decades have witnessed great advancements in multiobjective evolutionary
algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these …
algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these …
Genetic algorithm-based hyperparameter optimization of deep learning models for PM2.5 time-series prediction
Since air pollution negatively affects human health and causes serious diseases, accurate
air pollution prediction is essential regarding environmental sustainability. Although …
air pollution prediction is essential regarding environmental sustainability. Although …
Automatic design of machine learning via evolutionary computation: A survey
Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …
knowledge from data, has been widely applied to practical applications, such as …