Clasificador bayesiano de dos clases para seleccionar la mejor regla de prioridad en un problema Job Shop: Open Shop
Resumen
Autores/as
-
Omar Danilo Castrillón Gomez
Universidad Nacional de Colombia.
Omar Danilo Castrillón Gomez
Profesor titular, de la Universidad Nacional de Colombia. Con mas de 20 años de experiencia docente en el area de informatica, logistica, optimización. Ingeniero de Sistema. Especialista en Educacion personalizada, Gerencia y control de calidad, y en BioIngenieria, doctor en Bio Ingenieria de la Universidad Politecnica de Valencia - España.
Referencias
Baltazar, a., aranda, J. I. & Aguilar, G. G. (2008). Bayesian classification of ripening stages of tomato fruit using acoustic impact and colorimeter sensor data. computers and electronics in agriculture, No. 60, pp. 113-121.
Dallaire, P., Giguère, P., Émond, D. & Chaib-draa, B. (2014). Autonomous tactile perception: A combined improved sensing and Bayesian nonparametric approach. Robotics and Autonomous Systems, No. 62, pp. 422-435.
Del Sagrado, J., Sanchez, J. A., Rodriguez, F. & Berenguel, M. (2016). Bayesian networks for greenhouse temperature control. Journal of Applied Logic, http://dx.doi.org/10.1016/j.jal.2015.09.006, Article in press.
Duda, R. O., Hart, P. E., & Stork, D. G. (2001). Patter Classification. New York, Estados Unidos: John Wiley & Sons, Pagina 41.
Fernandez, E. (2016). Analisis de clasificadores Bayesianos. Argentina: Laboratorio de sistemas Inteligentes, Consultado 18 de febrero de 2006, disponible en http://materias.fi.uba.ar/7550/clasificadores-bayesianos.pdf
Hanen , B., Concha , B., Toro, C. & Larragaña, P. (2013). Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers. Artificial Intelligence in Medicine, No. 57, pp. 219-229.
He, L., Liu, B., Hu, D., Wen, Y., Wan, M. & Long, J. (2015). Motor Imagery EEG Signals Analysis Based on Bayesian Network with Gaussian Distribution. Neurocomputing, http://dx.doi.org/10.1016/j.neucom.2015.05.133 (Article in press).
Karabatak, M. (2015). A new classifier for breast cancer detection based on Naïve Bayesian. Measurement, No. 72, pp. 32-36.
Mujalli, R. O., Lopez, G. & Garach L. (2016). Bayes classifiers for imbalanced traffic accidents data sets. Accident Analysis and Prevention, No. 88, pp. 37-51.
Mukherjee, S. & Sharmaa, N. (2012). Intrusion Detection using Naive Bayes Classifier with Feature Reduction. Procedia Technology, No. 4, pp. 119-128.
Roy, S., Shivakumara, P., Roy, P. P., Pal, U., Tan, C. L. & Lu, T. (2015). Bayesian classifier for multi-oriented video text recognition system. Expert Systems with Applications, No. 42, pp. 5554-5556.
Salama, K. M. & Freitas. (2014). A. A. Classification with cluster-based Bayesian multi-nets using Ant Colony Optimization. Swarm and Evolutionary Computation, No. 18, pp. 54-70.
Sun, L., Lin, L., Wang, Y., Gen, M. & Kawakami, H. (2015). A Bayesian Optimization-based Evolutionary Algorithm for Flexible Job Shop Scheduling. Procedia Computer Science, No. 61, pp. 521-526.
Wiggins, M., Saad, A. & Litt, B. (2008). Vachtsevanos, G. Evolving a Bayesian classifier for ECG-based age classification in medical applications. Applied Soft Computing, No. 8, pp. 599-608.
Xiang, C., Yong, P. C. & Meng, L. S. (2008). Design of multiple-level hybrid classifier for intrusion detection system using Bayesian clustering and decision trees. Pattern Recognition Letters, No. 29, pp. 918-924.
Yin, W., Kissinger, J. C., Moreno, A., Galinski, M. R. & Styczynski. (2015). M. P. From genome-scale data to models of infectious disease: A Bayesian network-based strategy to drive model development. Mathematical Biosciences, No. 260, pp. 156-168.
Zaidan, A., Ahmad, N., Karim, H. A., Larbani, M., Zaidan & B. Sali. (2014). A. On themulti-agent learning neural and Bayesian methods in skin detector and pornography classifier: An automated anti-pornography system. Neurocomputing, No. 131, pp. 397-418.