Smart building's elevator with intelligent control algorithm based on Bayesian networks
Resumen
Implementation of the intelligent elevator control systems based on machine-learning algorithms should play an important role in our effort to improve the sustainability and convenience of multi-floor buildings. Traditional elevator control algorithms are not capable of operating efficiently in the presence of uncertainty caused by random flow of people. As opposed to conventional elevator control approach, the proposed algorithm utilizes the information about passenger group sizes and their waiting time, provided by the image acquisition and processing system. Next, this information is used by the probabilistic decision-making model to conduct Bayesian inference and update the variable parameters. The proposed algorithm utilizes the variable elimination technique to reduce the computational complexity associated with calculation of marginal and conditional probabilities, and Expectation- Maximization algorithm to ensure the completeness of the data sets. The proposed algorithm was evaluated by assessing the correspondence level of the resulting decisions with expected ones. Significant improvement in correspondence level was obtained by adjusting the probability distributions of the variables affecting the decision-making process. The aim was to construct a decision engine capable to control the elevators actions, in way that improves user's satisfaction. Both sensitivity analysis and evaluation study of the implemented model, according to several scenarios, are presented. The overall algorithm proved to exhibit the desired behavior, in 94% case of the scenarios tested. © 2013 The Science and Information (SAI) Organization.
Colecciones
Ítems relacionados
Mostrando ítems relacionados por Título, autor o materia.
-
Integrated Video and Acoustic Emission Data Fusion for Intelligent Decision Making in Material Surface Inspection System
Chernov A.V., Savvas I.K., Alexandrov A.A., Kartashov O.O., Polyanichenko D.S., Butakova M.A., Soldatov A.V. (2022)In the field of intelligent surface inspection systems, particular attention is paid to decision making problems, based on data from different sensors. The combination of such data helps to make an intelligent decision. ... -
Evolving cognitive and social experience in Particle Swarm Optimization through Differential Evolution: A hybrid approach
Epitropakis, M. G.; Plagianakos, V. P.; Vrahatis, M. N. (2012)In recent years, the Particle Swarm Optimization has rapidly gained increasing popularity and many variants and hybrid approaches have been proposed to improve it. In this paper, motivated by the behavior and the spatial ... -
Tournament selection algorithm for the multiple travelling salesman problem
Polychronis G., Lalis S. (2020)The multiple Travelling Salesman Problem (mTSP) is a generalization of the classic TSP problem, where the cities in question are visited using a team of salesmen, each one following a different, complementary route. Several ...