A novel bayesian optimization-based machine learning framework for COVID-19 detection from inpatient facility data
The whole world faces a pandemic situation due to the deadly virus, namely COVID-19. It
takes considerable time to get the virus well-matured to be traced, and during this time, it …
takes considerable time to get the virus well-matured to be traced, and during this time, it …
Using an artificial neural network for improving the prediction of project duration
I Lishner, A Shtub - Mathematics, 2022 - mdpi.com
One of the most challenging tasks in project management is estimating the duration of a
project. The unknowns that accompany projects, the different risks, the uniqueness of each …
project. The unknowns that accompany projects, the different risks, the uniqueness of each …
An informative path planner for a swarm of asvs based on an enhanced pso with gaussian surrogate model components intended for water monitoring applications
MJT Kathen, IJ Flores, DG Reina - Electronics, 2021 - mdpi.com
Controlling the water quality of water supplies has always been a critical challenge, and
water resource monitoring has become a need in recent years. Manual monitoring is not …
water resource monitoring has become a need in recent years. Manual monitoring is not …
[HTML][HTML] Learning locomotion skills in evolvable robots
G Lan, M van Hooft, M De Carlo, JM Tomczak… - Neurocomputing, 2021 - Elsevier
The challenge of robotic reproduction–making of new robots by recombining two existing
ones–has been recently cracked and physically evolving robot systems have come within …
ones–has been recently cracked and physically evolving robot systems have come within …
Learning adaptive differential evolution by natural evolution strategies
Adaptive parameter control is critical in the design and application of evolutionary algorithm
(EA), so does in differential evolution. In the past decade, many adaptive evolutionary …
(EA), so does in differential evolution. In the past decade, many adaptive evolutionary …
A Bayesian Optimization Approach for Tuning a Grouping Genetic Algorithm for Solving Practically Oriented Pickup and Delivery Problems
Background: The Multi Depot Pickup and Delivery Problem with Time Windows and
Heterogeneous Vehicle Fleets (MDPDPTWHV) is a strongly practically oriented routing …
Heterogeneous Vehicle Fleets (MDPDPTWHV) is a strongly practically oriented routing …
Controlling Sequential Hybrid Evolutionary Algorithm by Q-Learning [Research Frontier][Research Frontier]
Many state-of-the-art evolutionary algorithms (EAs) can be categorized as sequential hybrid
EAs, in which various EAs are sequentially executed. The timing to switch from one EA to …
EAs, in which various EAs are sequentially executed. The timing to switch from one EA to …
A comparison of pso-based informative path planners for autonomous surface vehicles for water resource monitoring
M Carolina Jara Ten Kathen, I Jurado Flores… - Proceedings of the …, 2022 - dl.acm.org
Preserving water resources is an objective that is constantly being pursued. Monitoring the
aquatic environments is an action to fulfill this objective, since the state of the water quality …
aquatic environments is an action to fulfill this objective, since the state of the water quality …
[HTML][HTML] Bundle selection approaches for collaborative practical-oriented pickup and delivery problems
Due to the increasing price pressure in the less-than-truckload (LTL) market, horizontal
cooperation is an effective and efficient way for small-and medium-sized LTL carriers to …
cooperation is an effective and efficient way for small-and medium-sized LTL carriers to …
Variational reinforcement learning for hyper-parameter tuning of adaptive evolutionary algorithm
The performance of an evolutionary algorithm (EA) is deeply affected by its control
parameter's setting. It has become a trend in recent studies to treat the control parameter as …
parameter's setting. It has become a trend in recent studies to treat the control parameter as …