Clasificador bayesiano de dos clases para seleccionar la mejor regla de prioridad en un problema Job Shop: Open Shop
Clasificador bayesiano de dos clases para seleccionar la mejor regla de prioridad en un problema Job Shop: Open Shop
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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.