RT Conference Proceedings
T1 Metadomotic Optimization Using Genetic Algorithms
A1 Merino-Córdoba, Salvador
A1 Martínez-del-Castillo, Javier
A1 Guzmán-Navarro, Francisco
K1 Domótica
K1 Algoritmos genéticos
AB New technologies applied in domotic allow us to extract plenty of data about the usual behavior of occupants in any installation. Discipline that works with these data for the pursuit of new knowledge is called Metadomotic.To achieve this learning and relationships between different data, we make use of the tools provided by artificial intelligence. Today the use of these techniques in solving problems is fully extended. Among the best known we will focus on the application of genetic algorithms, technical halfway between biology and mathematics, to try to resolve the issues raised in this paper.This article proposes the classification of domotic parameters to optimize an objective function. In a nutshell we will try two possible applications:1. The minimization of energy consumption through the classification of the parameters of use and consumption coefficients, inherent to each user and device2. The maximization of industrial production through the influence of environment parametersOnce established several basic suboptimal solutions, they will be combined randomly, through the crossover, mutation and cloning, to try to find the optimal.
YR 2014
FD 2014-07-17
LK http://hdl.handle.net/10630/7858
UL http://hdl.handle.net/10630/7858
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026