Spatio-temporal forecasting: A survey of data-driven models using exogenous data
Forecasting Spatio-Temporal processes has been attracting a great deal of interest within
the research community. In this context, there is an increasing trend of proposing and …
the research community. In this context, there is an increasing trend of proposing and …
Imputation of missing traffic flow data using denoising autoencoders
In transportation engineering, spatio-temporal data including traffic flow, speed, and
occupancy are collected from different kinds of sensors and used by transportation …
occupancy are collected from different kinds of sensors and used by transportation …
Optimizing the area coverage of networked uavs using multi-agent reinforcement learning
TA Tamba - … on Instrumentation, Control, and Automation (ICA), 2021 - ieeexplore.ieee.org
Wireless sensor networks (WSNs) have been widely used in various area coverage
applications which require the monitoring and surveillance of systems with spatiotemporally …
applications which require the monitoring and surveillance of systems with spatiotemporally …
Hyperparameter tuning to optimize implementations of denoising autoencoders for imputation of missing spatio-temporal data
Spatio-temporal data collected from sensors can sometimes have gaps where data is
missing. Transportation planners and engineers use such data to perform various different …
missing. Transportation planners and engineers use such data to perform various different …
A Multi-Agent Reinforcement Learning Approach for Spatiotemporal Sensing Application in Precision Agriculture
TA Tamba - Industry 4.0 in Small and Medium-Sized Enterprises …, 2022 - taylorfrancis.com
Digital transformations within the realm of Industry 4.0 have introduced a paradigm shift in
the management/production systems of small-and medium-sized enterprises (SMEs) in the …
the management/production systems of small-and medium-sized enterprises (SMEs) in the …