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English Information

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Authors
# Name
1 Dieinison Braga(dieinison@alu.ufc.br)
2 Ticiana Silva( ticianalc@gmail.com)
3 Atslands Roch(atslands@ufc.br)
4 Gustavo Coutinho(gustavolgcr@lia.ufc.br)
5 Regis Magalhães(regis@insightlab.ufc.br)
6 Paulo GuerraT.(paulodetarso@ufc.br)
7 Jose Macêdo(jose.macedo@insightlab.ufc.br)

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Reference
# Reference
1 Allen, R. G., Pereira, L. S., Raes, D., Smith, M., et al. (1998). Crop evapotranspirationguidelines for computing crop water requirements-fao irrigation and drainage paper 56. FAO, Rome, 300(9):D05109.
2 Box, G. E., Jenkins, G. M., Reinsel, G. C., and Ljung, G. M. (2015). Time series analysis: forecasting and control. John Wiley & Sons, New Jersey, USA.
3 Brockwell, P. J. and Davis, R. A. (2016). Introduction to time series and forecasting. Springer, Switzerland.
4 Caminha, H., Silva, T., Rocha, A., and Lima, S. (2017). Estimating reference evapotranspiration using data mining prediction models and feature selection. Proceedings of the 19th International Conference on Enterprise Information Systems (ICEIS 2017), 1:272–279.
5 James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013). An introduction to statistical learning, volume 112. Springer, New York, USA.
6 Legates, D. R. and McCabe, G. J. (1999). Evaluating the use of goodness-of-fit measures in hydrologic and hydroclimatic model validation. Water resources research, 35(1):233–241.
7 P. Avishek, P. P. (2017). Practical Time Series Analysis: Master Time Series Data Processing, Visualization, and Modeling using Python.
8 Packt, Birmingham, UK. Siami-Namini, S. and Namin, A. S. (2018). Forecasting economics and financial time series: Arima vs. lstm. arXiv preprint arXiv:1803.06386.
9 Smith, T. G. (2017). Pyramid: ARIMA estimators for Python. MIT, USA.
10 Tan, P.-N. et al. (2006). Introduction to data mining. Pearson Education India, India.
11 Thiago, H. F., Wagner, M. d. C., and Marcus, A. F. (2017). Atlas irrigação: uso da água na agricultura irrigada. Agência Nacional de Águas, Brasília, DF, Brasil.
12 Tseng, F.-M. and Tzeng, G.-H. (2002). A fuzzy seasonal arima model for forecasting. Fuzzy Sets and Systems, 126(3):367–376.
13 Wang, Y. and Witten, I. H. (1996). Induction of model trees for predicting continuous classes