SBBD

Paper Registration

1

Select Book

2

Select Paper

3

Fill in paper information

4

Congratulations

Fill in your paper information

English Information

(*) To change the order drag the item to the new position.

Authors
# Name
1 Bruna Capistrano(bruna.capistrano@aluno.cefet-rj.br)
2 Luma Chen(luma.chen@aluno.cefet-rj.br)
3 Matheus Ribeiro(matheus.ribeiro@aluno.cefet-rj.br)
4 Carla Pacheco(cpacheco@inf.puc-rio.br)
5 Dacy Lobosco(dacy.lobosco@cefet-rj.br)
6 João Quadros(joao.quadros@cefet-rj.br)
7 Maria Izabel Barreto(maizabel@petrobras.com.br)
8 Eduardo Ogasawara(eogasawara@ieee.org)

(*) To change the order drag the item to the new position.

Reference
# Reference
1 Box, G. E. P., Jenkins, G. M., Reinsel, G. C., and Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control. John Wiley & Sons.
2 Esling, P. and Agon, C. (2012). Time-series data mining. ACM Computing Surveys, 45(1).
3 FAO (2022). Food and Agriculture Organization of the United Nations. Technical report, http://www.fao.org.
4 Gomes, H. d. O., Menezes, J., da Costa, J., Coutinho, H., Teixeira, R., and do Nascimento, R. (2020). A socio-environmental perspective on pesticide use and food production. Ecotoxicology and Environmental Safety, 197.
5 Han, J., Kamber, M., and Pei, J. (2012). Data Mining: Concepts and Techniques.
6 Huang, G.-B., Zhou, H., Ding, X., and Zhang, R. (2012). Extreme learning machine for regression and multiclass classification. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 42(2):513–529.
7 Hyndman, R. J. and Athanasopoulos, G. (2018). Forecasting: principles and practice. OTexts. Júnior, D. d. O. S., Oliveira, J. d., and Neto, P. d. M. (2019). An intelligent hybridization of ARIMA with machine learning models for time series forecasting. Knowledge-Based Systems, 175:72–86.
8 Kitchin, R. and Lauriault, T. (2015). Small data in the era of big data. GeoJournal, 80(4):463–475.
9 Lee, G.-H. and Choi, K.-C. (2020). Adverse effects of pesticides on the functions of immune system. Comparative Biochemistry and Physiology Part - C: Toxicology and Pharmacology, 235.
10 Lindemann, B., Müller, T., Vietz, H., Jazdi, N., and Weyrich, M. (2021). A survey on long short-term memory networks for time series prediction. In Procedia CIRP, volume 99, pages 650–655.
11 Rao, C., Rahul, M., Dasgupta, S., and Hegde, R. (2021). Sustainable Pesticide usage in Agriculture. In 2021 IEEE Mysore Sub Section International Conference, MysuruCon 2021, pages 628–633.
12 Salles, R., Belloze, K., Porto, F., Gonzalez, P., and Ogasawara, E. (2019). Nonstationary time series transformation methods: An experimental review. Knowledge-Based Systems, 164:274– 291.
13 Shumway, R. H. and Stoffer, D. S. (2017). Time Series Analysis and Its Applications: With R Examples. Springer, New York, NY, 4 edition.
14 Siami-Namini, S., Tavakoli, N., and Siami Namin, A. (2019). A Comparison of ARIMA and LSTM in Forecasting Time Series. In Proceedings - 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018, pages 1394–1401.
15 Tilman, D., Cassman, K., Matson, P., Naylor, R., and Polasky, S. (2002). Agricultural sustainability and intensive production practices. Nature, 418(6898):671–677.
16 Tsay, R. S. (2010). Analysis of Financial Time Series. Wiley, Cambridge, Mass, 3 edition.
17 Yu, W., Han, X., Wang, Y., and Yang, J. (2020). Prediction of pesticide residues in agricultural products based on time series model in Chengdu, China. In IOP Conference Series: Earth and Environmental Science, volume 594.