4 research outputs found
Design and Implementation of Conchoid and Offset Processing Maple Packages
Annals of Mathematics and Artificial Intelligence presents a range of topics of concern to scholars applying quantitative, combinatorial, logical, algebraic and algorithmic methods to diverse areas of Artificial Intelligence, from decision support, automated deduction, and reasoning, to knowledge-based systems, machine learning, computer vision, robotics and planning
Development of a Decision Making Algorithm for Traffic Jams Reduction Applied to Intelligent Transportation Systems
This paper is aimed at developing a decision making algorithm for traffic jams reduction that can be applied to Intelligent Transportation Systems. To do so, these algorithms must address two main challenges that arise in this context. On one hand, there are uncertainties in the data received from sensor networks produced by incomplete information or because the information loses some of the precision during information processing and display. On the other hand, there is the variability of the context in which these types of systems are operating. More specifically, Analytic Hierarchy Process (AHP) algorithm has been adapted to ITS, taking into account the mentioned challenges. After explaining the proposed decision making method, it is validated in a specific scenario: a smart traffic management system
Desarrollo de algoritmos de toma de decisi贸n aplicados a las ciudades inteligentes
Este trabajo se enmarca dentro del 谩mbito de las Ciudades Inteligentes. Una Ciudad Inteligente se puede definir como aquella ciudad que usa las tecnolog铆as de la informaci贸n y las comunicaciones para hacer que tanto su infraestructura cr铆tica, como sus componentes y servicios p煤blicos ofrecidos sean m谩s interactivos, eficientes y los ciudadanos
puedan ser m谩s conscientes de ellos. Se trata de un concepto emergente que presenta una serie de retos de dise帽o que se deben abordar. Dos retos importantes
son la variabilidad del contexto con el tiempo y la incertidumbre en la informaci贸n del contexto.
Una parte fundamental de estos sistemas, y que permite abordar estos retos, son los mecanismos de toma de decisi贸n. Estos mecanismos permiten a los sistemas modificar
su comportamiento en funci贸n de los cambios que detecten en su contexto, de manera que puedan adaptarse y responder adecuadamente a la situaci贸n en cada momento.
Este trabajo tiene como objetivo el desarrollo de algoritmos de toma de decisi贸n en el marco de las Ciudades Inteligentes. En particular, se ha dise帽ado e implementado,
utilizando el software MATLAB, un algoritmo de toma de decisi贸n que aborda los retos mencionados y que se puede aplicar en una de las 谩reas que engloban las Ciudades
Inteligentes: los Sistemas Inteligentes de Transporte.
Este proyecto se estructura fundamentalmente en dos partes: una parte te贸rica y una parte pr谩ctica. En la parte te贸rica se trata de proporcionar al lector nociones b谩sicas
sobre los conceptos de Ciudad Inteligente y Sistemas Inteligentes de Transporte, as铆 como de la toma de decisi贸n. Tambi茅n se explican los pasos del procedimiento de la toma de decisi贸n y se proporciona un estado del arte de los algoritmos de toma de decisi贸n existentes.
Por otro lado, la segunda parte de este proyecto es totalmente original, y en ella el autor propone un algoritmo de toma de decisi贸n para ser aplicado en el 谩mbito de los Sistemas Inteligentes de Transporte y desarrolla la implementaci贸n en MATLAB del algoritmo
mencionado. Por 煤ltimo, para demostrar su funcionamiento, se valida el algoritmo en un escenario de aplicaci贸n consistente en un sistema inteligente de gesti贸n del tr谩fico.
ABSTRACT.
This master thesis is framed under Smart Cities environment. A Smart City can be defined as the use of Information and Communication Technologies to make the critical infrastructure components and services of a city more intelligent, interconnected and efficient and citizens can be also more aware of them. Smart City is a new concept
which presents a novel set of design challenges that must be addressed. Two important challenges are the changeable context and the uncertainty of context information.
One of the essential parts of Smart Cities, which enables to address these challenges, are decision making mechanisms. Based on the information collected of the context, these systems can be configured to change its behavior whenever certain changes are detected, so that they can adapt themselves and response to the current situation properly.
This master thesis is aimed at developing decision making algorithms under Smart Cities framework. In particular, a decision making algorithm which addresses the abovementioned
challenges and that can be applied to one of the main categories of Smart Cities, named Intelligent Transportation Systems, has been designed and implemented.
To do so, MATLAB software has been used.
This project is mainly structured in two parts: a theoretical part and a practical part.
In theoretical part, basic ideas about the concept of Smart Cities and Intelligent Transportation Systems are given, as well as the concept of decision making. The steps of the
decision making procedure are also explained and a state of the art of existing decision making algorithms is provided.
On the other hand, the second part of this project is totally original. In this part, the author propose a decision making algorithm that can be applied to Intelligent Transportation Systems and develops the implementation of the algorithm in MATLAB. Finally, to
show the operation of the algorithm, it is validated in an application scenario consisting in a smart traffic management system