A survey on deep learning: Algorithms, techniques, and applications
The field of machine learning is witnessing its golden era as deep learning slowly becomes
the leader in this domain. Deep learning uses multiple layers to represent the abstractions of …
the leader in this domain. Deep learning uses multiple layers to represent the abstractions of …
[HTML][HTML] Reinforcement learning in urban network traffic signal control: A systematic literature review
Improvement of traffic signal control (TSC) efficiency has been found to lead to improved
urban transportation and enhanced quality of life. Recently, the use of reinforcement …
urban transportation and enhanced quality of life. Recently, the use of reinforcement …
Continual learning through synaptic intelligence
While deep learning has led to remarkable advances across diverse applications, it
struggles in domains where the data distribution changes over the course of learning. In …
struggles in domains where the data distribution changes over the course of learning. In …
Big data deep learning: challenges and perspectives
XW Chen, X Lin - IEEE access, 2014 - ieeexplore.ieee.org
Deep learning is currently an extremely active research area in machine learning and
pattern recognition society. It has gained huge successes in a broad area of applications …
pattern recognition society. It has gained huge successes in a broad area of applications …
Computational intelligence in urban traffic signal control: A survey
Urban transportation system is a large complex nonlinear system. It consists of surface-way
networks, freeway networks, and ramps with a mixed traffic flow of vehicles, bicycles, and …
networks, freeway networks, and ramps with a mixed traffic flow of vehicles, bicycles, and …
Urban traffic signal control using reinforcement learning agents
This study presents a distributed multi-agent-based traffic signal control for optimising green
timing in an urban arterial road network to reduce the total travel time and delay experienced …
timing in an urban arterial road network to reduce the total travel time and delay experienced …
Distributed geometric fuzzy multiagent urban traffic signal control
Rapid urbanization and the growing demand for faster transportation has led to heavy
congestion in road traffic networks, necessitating the need for traffic-responsive intelligent …
congestion in road traffic networks, necessitating the need for traffic-responsive intelligent …
Real-time adaptive machine-learning-based predictive control of nonlinear processes
We present a machine learning-based predictive control scheme that integrates an online
update of the recurrent neural network (RNN) models to capture process nonlinear …
update of the recurrent neural network (RNN) models to capture process nonlinear …
An introduction to multi-agent systems
Multi-agent systems is a subfield of Distributed Artificial Intelligence that has experienced
rapid growth because of the flexibility and the intelligence available solve distributed …
rapid growth because of the flexibility and the intelligence available solve distributed …
Cloud computing for agent-based urban transportation systems
ZJ Li, C Chen, K Wang - IEEE intelligent systems, 2011 - ieeexplore.ieee.org
Agent-based traffic management systems can use the autonomy, mobility, and adaptability
of mobile agents to deal with dynamic traffic environments. Cloud computing can help such …
of mobile agents to deal with dynamic traffic environments. Cloud computing can help such …