[HTML][HTML] Particle swarm optimization algorithm and its applications: a systematic review
AG Gad - Archives of computational methods in engineering, 2022 - Springer
Throughout the centuries, nature has been a source of inspiration, with much still to learn
from and discover about. Among many others, Swarm Intelligence (SI), a substantial branch …
from and discover about. Among many others, Swarm Intelligence (SI), a substantial branch …
A survey on evolutionary neural architecture search
Deep neural networks (DNNs) have achieved great success in many applications. The
architectures of DNNs play a crucial role in their performance, which is usually manually …
architectures of DNNs play a crucial role in their performance, which is usually manually …
Major advances in particle swarm optimization: theory, analysis, and application
EH Houssein, AG Gad, K Hussain… - Swarm and Evolutionary …, 2021 - Elsevier
Over the ages, nature has constantly been a rich source of inspiration for science, with much
still to discover about and learn from. Swarm Intelligence (SI), a major branch of artificial …
still to discover about and learn from. Swarm Intelligence (SI), a major branch of artificial …
A stochastic configuration network based on chaotic sparrow search algorithm
C Zhang, S Ding - Knowledge-Based Systems, 2021 - Elsevier
Stochastic configuration network (SCN), as a novel incremental generation model with
supervisory mechanism, has an excellent superiority in solving large-scale data regression …
supervisory mechanism, has an excellent superiority in solving large-scale data regression …
Short-term prediction of lane-level traffic speeds: A fusion deep learning model
Accurate and robust short-term traffic prediction is an important part of advanced traveler
information systems. With the development of intelligent navigation and autonomous driving …
information systems. With the development of intelligent navigation and autonomous driving …
An improved Bayesian combination model for short-term traffic prediction with deep learning
Short-term traffic volume prediction, which can assist road users in choosing appropriate
routes and reducing travel time cost, is a significant topic of intelligent transportation system …
routes and reducing travel time cost, is a significant topic of intelligent transportation system …
An attention‐based deep learning model for traffic flow prediction using spatiotemporal features towards sustainable smart city
In the development of smart cities, the intelligent transportation system (ITS) plays a major
role. The dynamic and chaotic nature of the traffic information makes the accurate …
role. The dynamic and chaotic nature of the traffic information makes the accurate …
Automated traffic incident detection with a smaller dataset based on generative adversarial networks
An imbalanced and small training sample can cause an incident detection model to have a
low detection rate and a high false alarm rate. To solve the scarcity of incident samples, a …
low detection rate and a high false alarm rate. To solve the scarcity of incident samples, a …
TBSM: A traffic burst-sensitive model for short-term prediction under special events
Traffic prediction is an important management tool for traffic guidance and control and an
effective decision-making tool to help travelers plan routes and avoid congested road …
effective decision-making tool to help travelers plan routes and avoid congested road …
PSO-ELM: A hybrid learning model for short-term traffic flow forecasting
Accurate and reliable traffic flow forecasting is of importance for urban planning and
mitigation of traffic congestion, and it is also the basis for the deployment of intelligent traffic …
mitigation of traffic congestion, and it is also the basis for the deployment of intelligent traffic …