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Travel

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Design of Travel Route Identification and Scheduling System Based on Artificial Intelligence-Aided Image Segmentation.

Computational intelligence and neuroscience
This study designs a travel recognition and scheduling system using artificial intelligence and image segmentation techniques. To address the problem of low division quality of current point division algorithms, this study proposes a streaming graph ...

Construction of Tourism E-Commerce Platform Based on Artificial Intelligence Algorithm.

Computational intelligence and neuroscience
In the late twentieth century, with the rapid development of the Internet, e-commerce has emerged rapidly, which has changed the way people travel around the world. The greatest advantages of e-commerce are the flow of information and data and the im...

An Intelligent Recommendation Method for Tourist Attractions Based on Deep Learning.

Computational intelligence and neuroscience
Tourists are the people who can be seen all over the world. Therefore, this has increased the demand for product supply in tourist locations. Technological development would be the only solution to solve those issues related to the demand and supply ...

Multitask Learning with Graph Neural Network for Travel Time Estimation.

Computational intelligence and neuroscience
Travel time estimation (TTE) is widely applied for ride dispatching, ride-hailing, and route navigation. Even for a given trajectory, the travel time is affected by many spatial-temporal factors, including static ones such as distance, road type, and...

Solving the TSP by the AALHNN algorithm.

Mathematical biosciences and engineering : MBE
It is prone to get stuck in a local minimum when solving the Traveling Salesman Problem (TSP) by the traditional Hopfield neural network (HNN) and hard to converge to an efficient solution, resulting from the defect of the penalty method used by the ...

Graph-based representation for identifying individual travel activities with spatiotemporal trajectories and POI data.

Scientific reports
Individual daily travel activities (e.g., work, eating) are identified with various machine learning models (e.g., Bayesian Network, Random Forest) for understanding people's frequent travel purposes. However, labor-intensive engineering work is ofte...

Application of Machine Learning to Child Mode Choice with a Novel Technique to Optimize Hyperparameters.

International journal of environmental research and public health
Travel mode choice (TMC) prediction is crucial for transportation planning. Most previous studies have focused on TMC in adults, whereas predicting TMC in children has received less attention. On the other hand, previous children's TMC prediction stu...

Stochastic scheduling of autonomous mobile robots at hospitals.

PloS one
This paper studies the scheduling of autonomous mobile robots (AMRs) at hospitals where the stochastic travel times and service times of AMRs are affected by the surrounding environment. The routes of AMRs are planned to minimize the daily cost of th...

TransCode: Uncovering COVID-19 transmission patterns via deep learning.

Infectious diseases of poverty
BACKGROUND: The heterogeneity of COVID-19 spread dynamics is determined by complex spatiotemporal transmission patterns at a fine scale, especially in densely populated regions. In this study, we aim to discover such fine-scale transmission patterns ...