AIMC Topic: Travel

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Identification of COVID-19 can be quicker through artificial intelligence framework using a mobile phone-based survey when cities and towns are under quarantine.

Infection control and hospital epidemiology
We propose the use of a machine learning algorithm to improve possible COVID-19 case identification more quickly using a mobile phone-based web survey. This method could reduce the spread of the virus in susceptible populations under quarantine.

Gender and active travel: a qualitative data synthesis informed by machine learning.

The international journal of behavioral nutrition and physical activity
BACKGROUND: Innovative approaches are required to move beyond individual approaches to behaviour change and develop more appropriate insights for the complex challenge of increasing population levels of activity. Recent research has drawn on social p...

Assessment of factors affecting tourism satisfaction using K-nearest neighborhood and random forest models.

BMC research notes
OBJECTIVE: This study aimed to identify factors affecting the satisfaction of tourists traveling to the city of Hamadan as Asian urban tourism capital in 2018. The data a random sample of 300 tourists were collected using a designed questionnaire. We...

Multi-features taxi destination prediction with frequency domain processing.

PloS one
The traditional taxi prediction methods model the taxi trajectory as a sequence of spatial points. It cannot represent two-dimensional spatial relationships between trajectory points. Therefore, many methods transform the taxi GPS trajectory into a t...

An Application of Self-Organizing Map for Multirobot Multigoal Path Planning with Minmax Objective.

Computational intelligence and neuroscience
In this paper, Self-Organizing Map (SOM) for the Multiple Traveling Salesman Problem (MTSP) with minmax objective is applied to the robotic problem of multigoal path planning in the polygonal domain. The main difficulty of such SOM deployment is dete...

A Collaborative Location Based Travel Recommendation System through Enhanced Rating Prediction for the Group of Users.

Computational intelligence and neuroscience
Rapid growth of web and its applications has created a colossal importance for recommender systems. Being applied in various domains, recommender systems were designed to generate suggestions such as items or services based on user interests. Basical...

List-Based Simulated Annealing Algorithm for Traveling Salesman Problem.

Computational intelligence and neuroscience
Simulated annealing (SA) algorithm is a popular intelligent optimization algorithm which has been successfully applied in many fields. Parameters' setting is a key factor for its performance, but it is also a tedious work. To simplify parameters sett...

Solving the Traveling Salesman's Problem Using the African Buffalo Optimization.

Computational intelligence and neuroscience
This paper proposes the African Buffalo Optimization (ABO) which is a new metaheuristic algorithm that is derived from careful observation of the African buffalos, a species of wild cows, in the African forests and savannahs. This animal displays unc...

The Edge-Disjoint Path Problem on Random Graphs by Message-Passing.

PloS one
We present a message-passing algorithm to solve a series of edge-disjoint path problems on graphs based on the zero-temperature cavity equations. Edge-disjoint paths problems are important in the general context of routing, that can be defined by inc...

A Neural Network Approach to Intention Modeling for User-Adapted Conversational Agents.

Computational intelligence and neuroscience
Spoken dialogue systems have been proposed to enable a more natural and intuitive interaction with the environment and human-computer interfaces. In this contribution, we present a framework based on neural networks that allows modeling of the user's...